Methods Of Identification, Assessment, Prevention And Therapy Of Lung Diseases And Kits Thereof Including Gender-Based Disease Identification, Assessment, Prevention And Therapy

ABSTRACT

The invention provides biomarkers and combinations of biomarkers useful in diagnosing lung diseases such as non-small cell lung cancer or reactive airway disease. The invention also provides methods of differentiating ng disease, methods of monitoring therapy, and methods of predicting a subject&#39;s response to therapeutic intervention based on the extent of expression of the biomarkers and combinations of biomarkers. Kits comprising agents for detecting the biomarkers and combination of biomarkers are also provided.

BACKGROUND OF THE INVENTION (a) Field of the Invention

The invention relates to the detection, identification, assessment,prevention, diagnosis, and treatment of lung disease using biomarkersand kits thereof. More specifically, the invention relates to thediagnosis of non-small cell lung cancers and reactive airway diseases bymeasuring and quantifying expression levels of specific biomarkers. Theinvention also relates to the identification of biomarkers presentinhuman serum or other biological fluids which, when found to beexpressed at levels different from those found in the normal population,are indicative of pathologies associated with human lung tissues and thehuman respiratory system. By identifying the biomarkers associated withsuch pathologies, quantifying the expression levels of those biomarkers,and comparing the expression levels with those levels generally expectedto present in a normal person's serum, it is possible to detect thepresence of the pathologies early on in their progression through simpleblood tests and characterize the progression of the pathology, as wellas to differentiate among the pathologies.

(b) Description of the Related Art

Pathologies of the respiratory system, such as asthma and lung cancer,affect millions of Americans. In fact, the American Lung Association®reports that almost 20 million Americans suffer from asthma. TheAmerican Cancer Society, Inc. estimated 229,400 new cancer cases of therespiratory system and. 164,840 deaths from cancers of the respiratorysystem in 2007 alone. While the five year survival rate of all cancercases when the cancer is detected while still localized is 46%, the fiveyear survival rate of lung cancer patients is only 13%. Correspondingly.only 16% of lung cancers are discovered before the disease has spread.Lung cancers are generally categorized as two main types based on thepathology of the cancer cells. Each type is named for the types of cellsthat were transformed to become cancerous. Small cell lung cancers arederived from small cells in the human lung tissues, whereasnon-small-cell lung cancers generally encompass all lung cancers thatare not small-cell type. Non-small cell lung cancers are groupedtogether because the treatment is generally the same for allnon-small-cell types. Together, non-small-cell lung cancers, or NSCLCs,make up about 75% of all lung cancers.

A major factor in the low survival rate of lung cancer patients is thefact that lung cancer is difficult to diagnose early. Current methods ofdiagnosing lung cancer or identifying its existence in a human arerestricted to taking X-rays, Computed Tomography (CT) scans and sintests of the lungs to physically determine the presence or absence of atumor. Therefore, the diagnosis of lung cancer is often made only iresponse to symptoms which have presented for a significant period oftime, and after the disease has been present in the human long enough toproduce a physically detectable mass.

Similarly, current methods of detecting asthma are typically performedlong after the presentation of symptoms such as recurrent wheezing,coughing, and chest tightness. Current methods of detecting asthma aretypically restricted to lung function tests such as spirometry tests orchallenge tests. Moreover, these tests are often ordered by thephysician to be performed along with a multitude of other tests to ruleout other pathologies or reactive airway diseases such as chronicobstructive pulmonary disease (COPD), bronchitis, pneumonia, andcongestive heart failure.

There does not exist in the art a simple, reliable method of diagnosingpathologies of human lung tissues early in their development.Furthermore, there is not a blood test available today which is capableof indicating the presence of a particular lung tissue pathology. It istherefore desirable to develop a method to determine the existence oflung cancers early in the disease progression. It is likewise desirableto develop a method to diagnose asthma and non-small cell lung cancer,and to differentiate them from each other and from other lung diseasessuch as infections, at the earliest appearance of symptoms. It isfurther desirable to identify specific proteins present in human bloodwhich, when altered in terms of relative intensities of expression, areindicative of the presence of non-small cell lung cancers and/orreactive airway disease.

SUMMARY OF THE INVENTION

The present inventors have identified a number of biomarkers which areuseful for characterizing the physiologic state of a subject with regardto lung diseases, such as non-small cell lung cancer or reactive airwaydisease. These biomarkers are presented in Tables 1-23.

Table 1A lists biomarkers whose expression level has been found to bedifferent from the level in normal individuals when measured inindividual with one or more lung diseases. Table 1B lists biomarkerswhose expression level has been found to be different from the level innormal individuals when measured in individuals with either non-smallcell lung cancer or reactive airway disease, and to show a differentialexpression level between no small cell lung cancer and reactive airwaydisease. Table 1C lists biomarkers whose expression has been found to bedifferent from the level in normal individuals when measured inindividuals with non-small cell lung cancer or with reactive airwaydisease.

Table 2 lists biomarkers whose expression has been found to be differentfrom the level in normal individuals when measured in individuals withreactive airway disease. Table 3 lists biomarkers whose expression hasbeen and to be different from the level in normal individuals whenmeasured in individuals with non-small cell lung cancer. Table 4 listsbiomarkers whose expression levels have been found to be different whenmeasured between individuals with non-small cell lung cancer andreactive airway disease.

Table 5A lists biomarkers whose expression level has been found to bedifferent from the level in normal males when measured in males with oneor more lung diseases. Table 5B lists biomarkers whose expression levelhas been found to be different from the level in normal males whenmeasured in males with either non-small cell lung cancer or reactiveairway disease, and to show a differential expression level betweennon-small cell lung cancer and reactive airway disease. Table 5C listsbiomarkers whose expression has been found to be different from thelevel in normal males when measured in males with non-small cell lungcancer and reactive airway disease

Table 6 lists biomarkers whose expression has been found to be differentfrom the level in normal males when measured in males with reactiveairway disease. Table 7 lists biomarkers whose expression has been foundto be different from the level in normal males when measured in maleswith non-small cell lung cancer. Table 8 lists biomarkers whoseexpression levels have been found to be different when measured betweenmales with non-small cell lung cancer and reactive airway disease.

Table 9A lists biomarkers whose expression level has been found to bedifferent from the level in normal females when measured in females withone or more lung diseases. Table 9B lists biomarkers whose expressionlevel has been found to be different from the level in normal femaleswhen measured in females with either non-small cell lung cancer orreactive airway disease, and to show a differentia: expression levelbetweennon small cell lung cancer and reactive airway disease. Table 9Clists biomarkers whose expression has been found to be different fromthe level in normal females when measured in females itlx non-small celllung cancer and reactive airway disease.

Table 10 lists biomarkers whose expression has been found to bedifferent from the level in normal females when measured in females withreactive airway disease. Table 11 lists biomarkers whose expression hasbeen found to be different from the level in normal females whenmeasured in females with non-small cell lung cancer. Table 12 listsbiomarkers whose expression levels have been found to be different whenmeasured between females with non-small cell lung cancer and reactiveairway disease.

Table 13A lists biomarkers whose expression significantly differsbetween male and female reactive airway disease populations. Table 13Blists biomarkers whose expression does not significantly differ betweenmale and female reactive airway disease populations. Table 14A listsbiomarkers whose expression significantly differs between male andfemale non-small cell lung cancer populations. Table 14B listsbiomarkers whose expression does not significantly differ between maleand female non-small cell lung cancer populations. Table 15A listsbiomarkers ranked by relative standard deviation in fluorescenceintensity for the normal population. Table 15B lists biomarkers rankedby relative standard deviator in fluorescence intensity for the normalfemale population. Table 15C lists biomarkers ranked by relativestandard deviation in fluorescence intensity for the normal malepopulation.

Table 16A lists biomarkers whose expression level has been found to bedifferent from the level in normal males when measured in males with oneor more lung diseases. Table 16B lists biomarkers whose expression levelhas been found to be different from the level in normal males whenmeasured in males with either non-small cell lung cancer or reactiveairway disease, and to show a differential expression level betweennon-small cell lung cancer and reactive airway disease. Table 16C listsbiomarkers whose expression has been found to be different from thelevel in normal males when measured in males i non-small cell lungcancer and reactive airway disease.

Table 17 lists biomarkers whose expression has been found to bedifferent from the level in normal males when measured in males withreactive airway disease. Table 18 lists biomarkers whose expression hasbeen found to be different from the level in normal males when measuredin males with non-small cell lung cancer. Table 19 lists biomarkerswhose expression levels have been found to be different when measuredbetween males with non-small cell lung cancer and reactive airwaydisease.

Table 20A lists biomarkers whose expression level has been found to bedifferent from the level in normal females when measured in females withone or more diseases.

Table 20B lists biomarkers whose expression level has been found to bedifferent from the level in normal females when measured in females witheither non-small cell lung cancer or reactive airway disease, and toshow a differential expression level between non-small cell lung cancerand reactive airway disease. Table 20C lists biomarkers whose expressionhas been found to be different from the level in normal females whenmeasured in females with non-small cell lung cancer and reactive airwaydisease.

Table 21 lists biomarkers whose expression has been found be differentfrom the level in normal females when measured in females with reactiveairway disease. Table 22 lists biomarkers whose expression has beenfound to be different from the level in normal females when measured infemales with non-small cell lung cancer. Table 23 lists biomarkers whoseexpression levels have been found to be different when measured betweenfemales with non-small cell lung cancer and reactive airway disease.

Significance for Tables 1-15 were determined using the Student's t test.Significance for Tables 16-23 were determined using the Kruskal-Wallismethod.

Polypeptides comprising SEQ ID NOS: 1-17 are additional biomarkers whoseexpression has been found o change with one or more lung diseases.

The present invention provides various diagnostic, prognostic andtherapeutic methods which depend on the identification of thesebiomarkers.

The invention provides for a method of physiological characterization ina subject comprising determining the extent of expression of at leastone biomarker from any number of Tables 1-2 or 16-23 in a physiologicalsample of the subject, wherein the extent of expression of said at leastone biomarker is indicative of a lung disease, such as of non-small celllung cancer or reactive airway disease, or can assist in distinguishinglung diseases, such as of non-small cell lung cancer or reactive airwaydisease. The invention also provides for methods of physiologicalcharacterization in a subject comprising determining the extent ofexpression of at least one biomarker from Tables 13B, 14B, or 15B, whichalso appears on Tables 1-12 or 16-23 in a physiological sample of thesubject, preferably the biomarker is at least one of biomarker nos. 1-10of Tables 1-12 or 16-23, wherein the extent of expression of said atleast one biomarker is indicative of a lung disease, such as ofnon-small cell lung cancer or reactive airway disease. Alternatively, oradditionally, the extent of expression of the first order interactors ofthese biomarkers may be determined.

The invention provides for a method of physiological characterization ina subject comprising determining the extent of expression of SEQ ID NO:12 in a physiological sample of the subject, wherein the extent ofexpression of SEQ ID NO: 12 is indicative of a lung disease, such asnon-small cell lung cancer or reactive airway disease.

The invention provides for a method of physiological characterization ina subject comprising determining; the extent of expression of at leastone polypeptide selected from the group consisting of SEQ ID NOS: 1-17in a physiological sample of the subject, and determining the extent ofexpression of at least one biomarker from any number of Tables 1-12 or16-23, wherein the extent of expression of said least one polypeptideand said at least one biomarker from any number of Tables 1-12 or 16-23is indicative of a lung disease, such as non-small cell lung cancer orreactive airway disease.

The Invention provides for a method of diagnosing reactive airwaydisease in subject comprising determining the extent of expression atleast one biomarker from Table 2, Table 6, Table 10, Table 17, and Table21 in a physiological sample of the subject, wherein the extent ofexpression of said at least one biomarker is indicative of reactiveairway disease.

The invention provides for a method of diagnosing non-small cell lungcancer in a subject comprising determining the extent of expression atleast one biomarker from Table 3, Table 7, Table 11, Table 18, or Table22 in a physiological sample of the subject, wherein the extent ofexpression of said at least one biomarker is indicative of the presenceor development of non-small cell lung cancer.

The invention provides a diagnostic method to assist in differentiatingthe likelihood that a subject is at-risk of non-small cell lung canceror of reactive airway disease comprising determining the extent ofexpression of at least one biomarker from Table 4, Table 8, Table 12,Table 19, or Table 23 in a physiological sample of the subject who isat-risk for at least one of non-small cell lung cancer or reactiveairway disease, wherein the extent of expression of said at least onebiomarker from Table 4, Table 8, Table 12, Table 19, or Table 23 assistsin differentiating the likelihood that said subject is at-risk ofnon-small cell lung cancer or of reactive airway disease.

The invention provides a method for predicting the likelihood that asubject will respond to therapeutic intervention comprising determiningthe extent one expression of at least one biomarker described herein ina physiological sample of the subject, wherein the extent of expressionsof said at least one biomarker assists in predicting a subject'sresponse to said therapeutic intervention,

The invention also provides a method of monitoring a subject comprisingdetermining a first extent of expression of at least one biomarkerdescribed herein in a physiological sample of the subject, a secondextent of expression of said at least one biomarker in a physiologicalsample of the subject at a subsequent time to said first determination,and comparing said first extent of expression and said second extent ofexpression.

The invention also provides for methods of designing kits comprisingselecting at least one biomarker described herein, selecting a means fordetermining the extent of expression of said at least one biomarker, anddesigning a kit comprising said means for determining the eatenexpression.

The invention also provides for methods of designing kits comprisingselecting at least one biomarker described herein, selecting detectionagents for detecting said at: least one biomarker, and designing a kitcomprising said detection agents for detecting at least one biomarker.

The invention also provides kits comprising at least one biomarkerdescribed herein,

The invention also provides a kit comprising a means for determining theextent of expression of at least one polypeptide selected from the groupconsisting of SEQ ID NO: 12.

The invention also provides a kit comprising, detection agents fordetecting at least one polypeptide selected from the group consisting ofSEQ ID NO: 12.

The invention also provides a kit comprising, (a) means for determiningthe extent of expression of at least one polypeptide selected from thegroup consisting of SEQ ID NOS: 1-17, and (b) means for determining theextent of expression of at least one biomarker from anyone of Tables1-12 or Tables 16-23.

The invention also provides a kit comprising, (a) detection agents fordetecting at least one polypeptide selected from the group consisting ofSEQ ID NOS: 1-17, and (b) detection agents for detecting at least onebiomarker from anyone of Tables 1-12 or Tables 16-23.

The invention further provides for kits containing biomarkers and/orpolypeptides from a plurality of the above Tables.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A shows the average fluorescence intensity level of the biomarkersin the normal (NO) population from Example 1, as well as the standarddeviation and relative standard deviation.

FIG. 1B shows the average fluorescence intensity level of the biomarkersin the non-small cell lung cancer (LC) population from Example 1, aswell as the standard deviation and relative standard deviation.

FIG. 1C shows the average fluorescence intensity level of the biomarkersin the asthma EAST) population from Example 1, as well as the standarddeviation and relative standard deviation.

FIG. 1D shows the percent change in the mean of fluorescence intensityfor each of the biomarkers in the LC population v. NO population, ASTpopulation v. NO population, and the LC population v. AST populationfrom Example 1.

FIG. 1E shows the probability associated with Student's t valuesobtained by comparing the mean fluorescence intensity and variabilitymeasured for each biomarker in the populations from Example 1, where thepopulations to be compared are LC population v. NO population, ASTpopulation v. NO population, and the LC population v. AST population,respectively.

FIG. 2A shows the average fluorescence intensity level of the biomarkersin the normal (NO) population from Example 2, as well as the standarddeviation and relative standard deviation.

FIG. 2B shows the average fluorescence intensity level of the biomarkersin the non-small cell lung cancer (LC) population from Example 2, aswell as the standard deviation and relative standard deviation.

FIG. 2C shows the average fluorescence intensity level of the biomarkersin the asthma EAST) population from Example 2, as well as the standarddeviation and relative standard deviation.

FIG. 2D shows the percent change in the mean of fluorescence intensityfor each of the biomarkers in the LC population NO population ASTpopulation v. NO population, and the AST v. LC population from Example2.

FIG. 2E shows the probability associated with Student's t valuesobtained by comparing the mean fluorescence intensity and variabilitymeasured for each biomarker in the populations from Example 2, where thepopulations to be compared are LC population v. NO population, ASTpopulation v. NO population, and the AST population v. LC population,respectively.

FIG. 3A shows the average fluorescence intensity level of the biomarkersin the normal (NO) population from Example 3, as well as the standarddeviation and relative standard deviation.

FIG. 3B shows the average fluorescence intensity level of the biomarkersin tie non-small cell lung cancer (LC) population from Example 3, aswell as the standard deviation and relative standard deviation.

FIG. 3C shows the average fluorescence intensity level of the biomarkersin the asthma (AST)population from Example 3, as ell as the standarddeviation and relative standard deviation.

FIG. 3D shows the percent change in the mean of fluorescence intensityfor each of the biomarkers in the AST population v. NO population, LCpopulation v. NO populations, and the AST population v. LC populationfrom Example 3.

FIG. 3E shows the probability associated with Student's t valuesobtained by comparing the mean fluorescence intensity and variabilitymeasured for each biomarker in the populations from Example 3, where thepopulations to be compared are AST population v. NO population, LCpopulation v. NO population, and the AST v. LC population, respectively.

FIG. 4A shows the average fluorescence intensity level of the biomarkersin the normal (NO) female population from Example 3, as well as thestandard deviators: and relative standard deviation.

FIG. 4B shows the average fluorescence intensity level of the biomarkersin the non-small cell lung cancer (LC) female population from Example 3,as well as the standard deviation and relative standard deviation.

FIG. 4C shows the average fluorescence intensity level of the biomarkersin the asthma (AST) female population from Example 3, as well as thestandard deviation and relative standard deviation.

FIG. 4D shows the percent change in the mean of fluorescence intensityfor each of the biomarkers in the AST population v. NO femalepopulation, LC population v. NO female population, and the ASTpopulation v. LC female population from Example 3.

FIG. 4E shows the probability associated with Student's t valuesobtained by comparing the mean fluorescence intensity and variabilitymeasured for each biomarker in the female populations from Example 3,where the populations to be compared are AST population v. NO femalepopulation, LC population v. NO female population, and the ASTpopulation v. LC female population, respectively.

FIG. 5A shows the average fluorescence intensity level of the biomarkersin the normal (NO) male population from Example 3, as well as thestandard deviation and relative standard deviation.

FIG. 5B shows the average fluorescence intensity level of the biomarkersin the non-small cell lung cancer (LC) male population from Example 3,as well as the standard deviation and relative standard deviation.

FIG. 5C shows the average fluorescence intensity level of the biomarkersin the asthma (AST) male population from Example 3, as well as thestandard deviation and relative standard deviation.

FIG. 3D shows the percent change in the mean of fluorescence intensityfor each of the biomarkers in the AST population v. NO male population,LC population v. NO male population, and the AST population v. LC malepopulation Example 3.

FIG. 5E shows the probability associated with Student's t valuesobtained by comparing the mean fluorescence intensity and variabilitymeasured for each biomarker in the male populations from Example 3,where the populations to be compared are AST v. NO male populations, LCv. NO male populations, and the LC v. AST male populations,respectively.

FIG. 6A shows the percent change in the mean of fluorescence intensityfor each of the biomarkers in the AST male population compared to theAST female population, the LC male population compared to the LC femalepopulation, and the NO male population compared to the NO femalepopulation from Example 3.

FIG. 6B shows the probability associated with Student's t valuesobtained by comparing the mean fluorescence intensity and variabilitymeasured for each biomarker in the male and female populations fromExample 3, where the populations to be compared are the AST male andfemale populations, LC male and female populations, and the NO male andfemale populations, respectively.

FIG. 7A shows the percent change in the mean concentration of each ofthe biomarkers in the LC v. NO female populations, AST v. NO femalepopulations, and the AST v. LC female populations of Example 3.

FIG. 7B shows the probability associated with the kruskal-Wallis testcalculated by comparing the concentration measured for each biomarker inthe female populations of

Example 3, where the populations to be compared are AST v. NO femalepopulations, v. NO female populations, and the AST v. LC femalepopulations, respectively.

FIG. 8A shows the percent change in the mean concentration of each ofthe biomarkers in the LC v. NO male populations, AST v. NO malepopulations, and the AST v. LC male populations of Example 3.

FIG. 8B shows the probability associated with the Kruskal-Wallis testcalculated by comparing the concentration measured for each biomarker inthe male populations of Example 3, where the populations to be comparedare AST v. NO male populations, LC v. NO male populations, and the ASTv. LC male populations, respectively.

FIG. 9 shows relationships between the biomarkers of Table 16B.

DETAILED DESCRIPTION OF THE INVENTION

The invention relates to various methods of detection, identification,assessment, prevention, diagnosis, and treatment of lung disease usingbiomarkers including gender-based disease detection, identification,assessment, prevention, and diagnosis, and treatment. These methodsinvolve determining the extent of expression of specific biomarkers forwhich an altered expression is indicative of non-small cell lung cancerand/or reactive airway disease (e.g., asthma, chronic obstructivepulmonary disease, etc.). The invention also provides for various kitscomprising detection agents for detecting these biomarkers, or means fordetermining the extent of expression of these biomarkers.

Definitions

As used herein, a “biomarker” or “marker” is a biological molecule thatis objectively measured as a characteristic indicator of thephysiological status of a biological system. For purposes of the presentdisclosure biological molecules include ions, small molecules, peptides,proteins, pep d proteins bearing post-translational modifications,nucleosides nucleotides and polynucleotides including RNA and DNA,glycoproteins, lipoproteins, as well as various covalent andnon-covalent modifications of these types of molecules. Biologicalmolecules include any of these entities native to, characteristic of,and/or essential to the function of a biological system. The majority ofbiomarkers are polypeptides, although they may also be mRNA or modifiedmRNA which represents the pre-translation form of the gene productexpressed as the polypeptide, or hey may include post-translationalmodifications of the polypeptide.

As used herein, a “subject” means any animal, but is preferably amammal, such as, for example, a human, in many embodiments, the subjectwill be a human patient having, or at-risk of having, a lung disease.

As used herein, a “physiological sample” includes samples frombiological fluids and tissues. Biological fluids include whole blood,blood plasma, blood serum, sputum, urine, sweat, lymph, and alveolarlavage. Tissue samples include biopsies from solid lung tissue or othersolid tissues, lymph node biopsy tissues, biopsies of metastatic foci.Method of obtaining physiological samples are ell known.

As used herein, “therapeutic intervention” includes administration ofone or more therapeutic agents such as a small molecule ormacromolecule, radiation, surgery, or any combinations thereof.

As used herein, “detection agents” include reagents and systems thatspecifically detect the biomarkers described herein. Detection agentsdude reagents such as antibodies, nucleic acid probes, aptamers,lectins, or other reagents that have specific affinity for a particularmarker or markers sufficient to discriminate between the part liarmarker and other markers which might be in samples of interest, andsystems such as sensors, including sensors making use of bound orotherwise immobilized ligands as described above.

Identification of Biomarkers

The biomarkers of the invention were identified using two methods.First, identification of biomarkers indicative of non-small cell lungcancers and/or asthma was made by comparing the measured expressionlevels of fifty-nine selected biomarkers in the plasma of patients frompopulations who had been diagnosed with those respective pathologies toa population who had not been diagnosed with the pathologies, asconfirmed by a physician. This method is detailed in Examples 1-3.

Second, biomarkers were identified using mass spectrometry.Identification of proteins indicative of non-small cell lung cancersand/or asthma was made by comparing the mass spectral data for trypticpeptide digests of samples obtained from patients in differentphysicological states. In particular, the data as the mass of peptidefragments, represented as graphical indications of the intensities ofthe pseudo or protonated molecular ion signals of peptides and proteinscontaining those fragments expressed across time in a single dimension.The expression levels of thousands of proteins were compared, resultingin the identification of seventeen proteins which were expressed insubstantially differing intensities between populations of individualsnot g any diagnosed lung tissue pathologies, populations of individualshaving asthma, as diagnosed by a physician, and populations ofindividuals having non-small cell lung cancers, as diagnosed by aphysician. This method is detailed in Examples 6 and 7.

First Order Interactors

To promote and control the multitude of cellular and organismalphysiological functions necessary to maintain life, biological moleculesmust interact with each other. These interactions can be considered atype of communication. In this communication the various biologicalmolecules can be considered messages. These molecules, as a necessarypart of their signal transduction functions, necessarily interact with abroad variety of targets including other types of biological molecules.

One type of interacting molecule is commonly known as a receptor.Another type of direct intermolecular interaction is the in binding of aco-factor to an enzyme. These intermolecular interactions form networksof signaling molecules that work together to carry out and control tileessential life functions of cells and organisms. The particularbiomarkers of this invention are linked physiologically to otherbiomarkers whose level increases or decreases in a fashion coordinatedwith the level of particular biomarkers. These other biomarkers arecalled “first order interactors” with respect to the particularbiomarkers of the invention.

“First order interactors” are those molecular entities that interactdirectly with a particular biological molecule. For instance the drugmorphine interacts directly with opiate receptors resulting ultimatelyin the diminishment of the sensation of pain. Thus, the opiate receptorsare first order interactors under the definition of “first orderinteractors.” First order interactors include both upstream anddownstream direct neighbors for said biomarkers in the communicationpathways in which they interact. These entities encompass proteins,nucleic acids and small molecules which inlay be connected byrelationships that include but are not limited to direct (or indirect;regulation, expression, chemical reaction, molecular synthesis, finding,promoter binding, protein modification and molecular transport. Groupsof biomarkers whose levels are coordinated are well known to thoseskilled in the art and those knowledgeable in physiology and cellularbiology. Indeed, first order interactors for a particular biomarker areknown the art and can found using various databases and availablebioinformatics software such as ARIADNE PATHWAY STUDIO, ExPASYProteomics Server Qlucore Omics Explorer, Protein Prospector, PQuad,ChEMBL, and others. (as, ARIADNE PATHWAY STUDIO, Ariadne<www.ariadne.genomics.com> or ChEMBL Database, European BioinformaticsInstitute, European Molecular Biology Laboratory, <www.ebi.ac.uk>).

When the levels of the particular biomarkers of this invention areabnormal, levels of first order interactors biomarkers whose expressionis coordinated with the particular biomarkers are also abnormal.Therefore, determination that levels of a particular biomarker areabnormal may be accomplished by measuring the level of a first orderinteractors coordinated therewith. The skilled person will of courseconfirm that the level of a first order interactors which is used inlieu or in addition to a particular biomarker will vary in a defined andreproducible way consistent with the behavior of the particularbiomarker.

The invention provides that for any of the methods described herein, themethods to be performed with a particular biomarker may alternatively beperformed with the first order interactors of that particular biomarker.For example, the invention provides for methods of physiologicalcharacterization comprising determining the extent of expression of HGF.As such, the invention also provides for methods of physiologicalcharacterization comprising determining the extent of expression of afirst order interactors of HGF. The first order interactors of HGFinclude, but are not limited to those identified in Example 12.

Tables Identifying Significant Biomarkers

Table 1A lists biomarkers whose expression levels have a significant ormarginally significant difference between at least one of AST v. NOpopulations, LC v. NO populations, and AST v. LC populations.Significance was determined as shown in Examples 1-3 gassing Student's ttest. Markers are listed in descending order based on the significanceand magnitude of the difference in fluorescence intensity.

TABLE 1A SIGNIFICANT BIOMARKERS FOR LUNG DISEASE No. Biomarker 1 IL-13 2I-TAC 3 MCP-1 4 MMP-1 5 MPO 6 HGF 7 Eotaxin 8 MMP-9 9 MMP-7 10 IP-10 11SAA 12 Resistin 13 IL-5 14 Leptin 15 sVCAM-1 16 Adiponectin 17 CRP 18C-Peptide 19 MMP-3 20 SAP 21 IL-1ra 22 IL-15 23 EGF 24 IL12 (p70) 25MMP-8 26 IL-8 27 IL-6 28 MMP-12 29 PAI-1 30 Amylin (Total) 31 IL-1α 32sFSl 33 IL-4 34 MIP-1β 35 IL-10 36 SE-selectin 37 IL-17 38 GM-CSF 39G-CSF 40 TGF-α 41 IFN-γ 42 Fractalkine 43 VEGF 44 IL-7 45 IL-12 (p40) 46Sfas 47 MIF 48 IL-1β 49 IL-2 50 MIP-1α 51 Insulin 52 GLP-1 53 sCD40ligand

Table 1B lists biomarkers whose expression levels have a significantdifference between the AST v. NO populations, LC v. NO populations, andAST v. LC populations. Significance was determined as shown Examples 1-3using a Student's t test. Marginally significant biomarkers are notincluded. Markers are listed in descending order based on the magnitudeof the difference in fluorescence intensity.

TABLE 1B SIGNIFICANT BIOMARKERS FOR LUNG DISEASE No. Biomarker 1 IL-13 2I-TAC 3 MCP-1 4 MMP-1 5 MPO 6 HGF 7 Eotaxin 8 MMP-9 9 MMP-7 10 IP-10 11SAA 12 Resistin 13 IL-5 14 Leptin 15 sVCAM-1 16 Adiponectin 17 CRP 18C-Peptide 19 MMP-3 20 SAP 21 IL-1ra 22 IL-15

Table 1C lists biomarkers whose expression levels have a significant ormarginally significant difference between the AST v. NO populations andLC v. NO populations. Significance was determined as shown in Examples1-3 using a Student's t test. Markers are listed in descending orderbased on the magnitude of the difference in fluorescence intensity.

TABLE 1C SIGNIFICANT BIOMARKERS FOR LUNG DISEASE No. Biomarker 1 EGF 2IL12 (p70) 3 IL-8 4 IL-6 5 MMP-12 6 PAI-1 7 Amylin (Total) 8 IL-4 9MIP-1β 10 IL-10 11 SE-selectin 12 IL-17 13 GM-CSF 14 G-CSF 15 TGF-α 16IFN-γ 17 Fractalkine 18 VEGF 19 IL-12 (p40) 20 IL-7 21 Insulin

Table 2 lists biomarkers whose expression levels have a significant ormarginally significant difference between the AST v. NO populations.Significance was determined as shown in Examples 1-3 using a Student's ttest. Markers are listed in descending order based on the magnitude ofthe difference in fluorescence intensity.

TABLE 2 SIGNIFICANT BIOMARKERS INDICATIVE OF REACTIVE AIRWAY DISEASE No.Biomarker 1 IL-13 2 I-TAC 3 EGF 4 MCP-1 5 HGF 6 MPO 7 IL12 (p70) 8 MMP-99 IL-8 10 Eotaxin 11 IL-6 12 IP-10 13 IL-1α 14 PAI-1 15 Resistin 16 sFSl17 IL-5 18 Amylin (Total) 19 MMP-1 20 MMP-12 21 IL-4 22 SAA 23 MMP-7 24IL-7 25 sVCAM-1 26 SE-selectin 27 Leptin 28 Adiponectin 29 IL-17 30 CRP31 GM-CSF 32 MIP-1β 33 TGF-α 34 IL-10 35 Fractalkine 36 IFN-γ 37C-Peptide 38 VEGF 39 G-CSF 40 IL-1ra 41 IL-15 42 MMP-3 43 IL-12 (p40) 44SAP 45 Insulin

Table 3 lists biomarkers whose expression levels have a significant ormarginally significant difference between the LC v. NO populations.Significance was determined as shown in Examples 1-3 using a Student's ttest. Markers are listed in descending order based on the magnitude ofthe difference in fluorescence intensity.

TABLE 3 SIGNIFICANT BIOMARKERS FOR NON- SMALL CELL LUNG CANCER (NSCLC)No. Biomarker 1 IL-13 2 EGF 3 I-TAC 4 MMP-1 5 IL12 (p70) 6 Eotaxin 7MMP-8 8 MCP-1 9 MPO 10 IP-10 11 SAA 12 HGF 13 MMP-9 14 MMP-12 15 Amylin(Total) 16 PAI-1 17 MMP-7 18 IL-6 19 MIP-1β 20 Adiponectin 21 IL-10 22CRP 23 Resistin 24 MIF 25 IL-5 26 IL-4 27 Leptin 28 SE-selectin 29MIP-1α 30 C-Peptide 31 IL-1ra 32 SAP 33 G-CSF 34 IL-17 35 MMP-3 36 IFN-γ37 TGF-α 38 sVCAM-1 39 IL-15 40 GM-CSF 41 Fractalkine 42 IL-1β 43 VEGF44 GLP-1 45 IL-7 46 Insulin 47 IL-12 (p40) 48 IL-8

Table 4 lists biomarkers whose expression levels have a significant ormarginally significant difference between the AST v. LC populations.Significance was determined as shown in Examples 1-3 using a Student's ttest. Markers are listed in descending order based on the magnitude ofthe difference in fluorescence intensity.

TABLE 4 SIGNIFICANT BIOMARKERS DISTINGUISHING BETWEEN REACTIVE AIRWAYDISEASE AND NSCLC No. Biomarker 1 MMP-7 2 MMP-1 3 SAA 4 MMP-8 5 IL-8 6MCP-1 7 Leptin 8 IL-1α 9 HGF 10 I-TAC 11 sVCAM-1 12 MPO 13 sFSl 14C-Peptide 15 IL-13 16 Resistin 17 MMP-3 18 IL-5 19 SAP 20 Eotaxin 21MMP-9 22 CRP 23 Adiponectin 24 IP-10 25 IL-1ra 26 Sfas 27 IL-2 28 IL-1529 IL12 (p70) 30 IL-6 31 sCD40 ligand 32 VEGF

Table 5A lists biomarkers whose expression levels have a significant ormarginally significant difference between at least one of AST v. NO malepopulations, LC v. NO male populations, and AST v. LC male populations.Significance was determined as shown in Examples 1-3 using a Student's ttest. Markers are listed in descending order based on the significanceand magnitude of the difference in fluorescence intensity.

TABLE 5A SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE MALE POPULATIONNo. Biomarker 1 I-TAC 2 MPO 3 HGF 4 MMP-1 5 MMP-8 6 Eotaxin 7 IL-8 8MMP-7 9 PAI-1 10 IP-10 11 sVCAM-1 12 IL-10 13 Adiponectin 14 SAP 15IFN-γ 16 IL-13 17 EGF 18 MCP-1 19 MIF 20 IL-12(p70) 21 MMP-9 22 IL-6 23Amylin (Total) 24 SAA 25 IL-1α 26 TNF-α 27 IL-5 28 Resistin 29 IL-1β 30IL-7 31 IL-4 32 MIP-1β 33 Leptin 34 GM-CSF 35 G-CSF 36 TGF-α 37 IL-17 38CRP 39 IL-15 40 VEGF 41 Fractalkine 42 MMP-3 43 IL-12 (p40) 44 C-Peptide45 IL-1ra 46 GLP-1 47 MIP-1α 48 sFSl 49 Insulin 50 Sfas 51 SE-selectin52 MMP-12

Table 5B lists biomarkers whose expression levels have a significantdifference between the AST v. NO male populations, LC v. NO malepopulations, and AST v. LC male populations. Significance was determinedas shown in Examples 1-3 using a Student's t test. Marginallysignificant biomarkers are not included. Markers are listed indescending order based on the magnitude of the difference influorescence intensity.

TABLE 5B SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE MALE POPULATIONNo. Biomarker 1 I-TAC 2 MPO 3 HGF 4 MMP-1 5 MMP-8 6 Eotaxin 7 IL-8 8MMP-7 9 PAI-1 10 IP-10 11 sVCAM-1 12 IL-10 13 Adiponectin 14 SAP 15IFN-γ

Table 5C lists biomarkers whose expression levels have a significant ormarginally significant difference between the AST v. NO male populationsand LC v. NO male populations. Significance was determined as shown inExamples 1-3 using; a Student's t test. Markers are listed in descendingorder based on the magnitude of the difference in fluorescenceintensity.

TABLE 5C SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE MALE POPULATIONNo. Biomarker 1 IL-13 2 EGF 3 MCP-1 4 MIF 5 IL-12(p70) 6 MMP-9 7 IL-6 8TNF-α 9 IL-5 10 Resistin 11 IL-1β 12 IL-7 13 IL-4 14 MIP-1β 15 Leptin 16GM-CSF 17 G-CSF 18 TGF-α 19 IL-17 20 IL-15 21 VEGF 22 Fractalkine 23IL-12 (p40) 24 MIP-1α

Table 6 lists biomarkers whose expression levels have a significant ormarginally significant difference between the AST v. NO malepopulations. Significance was determined as shown in Examples 1-3 usinga Student's t test. Markers are listed in descending order based on themagnitude of the difference in fluorescence intensity.

TABLE 6 SIGNIFICANT BIOMARKERS FOR REACTIVE AIRWAY DISEASE IN THE MALEPOPULATION No. Biomarker 1 IL-13 2 I-TAC 3 MPO 4 HGF 5 EGF 6 MCP-1 7IL-8 8 MIF 9 IL-6 10 MMP-9 11 IL-12(p70) 12 Eotaxin 13 IL-1α 14 PAI-1 15MMP-8 16 TNF-α 17 IL-5 18 MMP-1 19 IL-1β 20 sFSl 21 Resistin 22 IL-7 23IL-4 24 IP-10 25 MIP-1β 26 GM-CSF 27 G-CSF 28 TGF-α 29 Leptin 30 IL-1731 sVCAM-1 32 GLP-1 33 IL-15 34 MMP-7 35 VEGF 36 IL-10 37 Fractalkine 38IL-12 (p40) 39 IFN-γ 40 Adiponectin 41 SE-selectin 42 SAP 43 MIP-1α

Table 7 lists biomarkers whose expression levels have a significant ormarginally significant difference between the LC v. NO male populations.Significance was determined as shown in Examples 1-3 using a Student's ttest. Markers are listed in descending order based on the magnitude ofthe difference in fluorescence intensity.

TABLE 7 SIGNIFICANT BIOMARKERS FOR NSCLC IN THE MALE POPULATION No.Biomarker 1 IL-13 2 I-TAC 3 EGF 4 MPO 5 HGF 6 MMP-1 7 MMP-8 8 MIF 9Eotaxin 10 IL-12(p70) 11 MCP-1 12 MMP-9 13 PAI-1 14 SAA 15 IP-10 16Amylin (Total) 17 MMP-7 18 Resistin 19 IL-6 20 MIP-1β 21 TNF-α 22 Leptin23 IL-8 24 IL-5 25 CRP 26 IL-10 27 Adiponectin 28 IL-7 29 IL-4 30 MMP-331 G-CSF 32 MIP-1α 33 IL-17 34 IFN-γ 35 IL-1ra 36 C-Peptide 37 TGF-α 38IL-15 39 Fractalkine 40 IL-1β 41 GM-CSF 42 sVCAM-1 43 SAP 44 VEGF 45IL-12 (p40) 46 Insulin 47 MMP-12

Table 8 lists biomarkers whose expression levels have a significant ormarginally significant difference between the AST v. LC malepopulations. Significance was determined as shown in Examples 1-3 usinga Student's t test. Markers are listed in descending order based on themagnitude of the difference in fluorescence intensity.

TABLE 8 SIGNIFICANT BIOMARKERS DISTINGUISHING BETWEEN REACTIVE AIRWAYDISEASE AND NSCLC IN THE MALE POPULATION No. Biomarker 1 MMP-1 2 MMP-8 3MMP-7 4 Amylin (Total) 5 SAA 6 IL-8 7 Insulin 8 IL-1α 9 sVCAM-1 10 IP-1011 CRP 12 MPO 13 MMP-3 14 Eotaxin 15 SAP 16 HGF 17 C-Peptide 18 I-TAC 19Sfas 20 PAI-1 21 IL-1ra 22 Adiponectin 23 IFN-γ 24 IL-10 25 GLP-1 26IL-6 27 IL-13 28 IL-15

Table 9A lists biomarkers whose expression levels have a significant ormarginally significant difference between at least one of AST v. NOfemale populations, LC v. NO female populations, and AST v. LC femalepopulations. Significance was determined as shown in Examples 1-3 usinga Student's t test. Markers are listed in descending order based on thesignificance and magnitude of the difference in fluorescence intensity.

TABLE 9A SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE FEMALEPOPULATION No. Biomarker 1 I-TAC 2 Leptin 3 IP-10 4 MMP-7 5 SAA 6 MPO 7Eotaxin 8 MMP-9 9 Adiponectin 10 CRP 11 C-Peptide 12 sVCAM-1 13 IL-15 14IL-1ra 15 IL-13 16 EGF 17 IL-12(p70) 18 MCP-1 19 MMP-1 20 HGF 21 IL-8 22Resistin 23 sFSl 24 PAI-1 25 MIF 26 SE-selectin 27 G-CSF 28 SAP 29 MMP-330 GM-CSF 31 sICAM-1 32 TNF-α 33 IL-10 34 MIP-1β 35 IL-1α 36 sCD40ligand 37 IL-6 38 MMP-12 39 MMP-2 40 IL-5 41 IL-4 42 Sfas 43 MMP-8 44IL-1β 45 IL-12 (p40) 46 IL-2 47 VEGF 48 TGF-α 49 IFN-γ 50 GLP-1 51Amylin (Total) 52 Insulin

Table 9B lists biomarkers whose expression levels have a significantdifference between the AST v. NO female populations, LC v. NO femalepopulations, and AST v. LC female populations. Significance wasdetermined as shown in Examples 1-3 using a Student's t test. Marginallysignificant biomarkers are not included. Markers are listed indescending order based on the magnitude of the difference influorescence intensity.

TABLE 9B SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE FEMALEPOPULATION No. Biomarker 1 I-TAC 2 Leptin 3 IP-10 4 MMP-7 5 SAA 6 MPO 7Eotaxin 8 MMP-9 9 Adiponectin 10 CRP 11 C-Peptide 12 sVCAM-1 13 IL-15 14IL-1ra

Table 9C lists biomarkers whose expression levels have a significant ormarginally significant difference between die AST v. NO femalepopulations and LC v. NO female populations. Significance was determinedas shown in Examples 1-3 using a Student's test. Markers are listed indescending order based on the magnitude of the difference influorescence intensity.

TABLE 9C SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE FEMALEPOPULATION No. Biomarker 1 IL-13 2 EGF 3 IL-12(p70) 4 MCP-1 5 PAI-1 6MIF 7 SE-selectin 8 G-CSF 9 GM-CSF 10 sICAM-1 11 IL-2 12 TGF-α

Table 10 lists biomarkers whose expression levels have a significant ormarginally significant difference between the AST v. NO femalepopulations. Significance was determined as shown in Examples 1-3 usinga Student's t test. Markers are listed in descending order based on themagnitude of the difference in fluorescence intensity.

TABLE 10 SIGNIFICANT BIOMARKERS FOR REACTIVE AIRWAY DISEASE IN THEFEMALE POPULATION No. Biomarker 1 IL-13 2 I-TAC 3 EGF 4 MCP-1 5 Leptin 6IL-12(p70) 7 IP-10 8 MPO 9 HGF 10 MMP-9 11 Eotaxin 12 SAA 13 Resistin 14sFSl 15 PAI-1 16 MMP-2 17 MMP-7 18 CRP 19 sCD40 ligand 20 MIF 21SE-selectin 22 sVCAM-1 23 IL-5 24 C-Peptide 25 IL-4 26 Adiponectin 27Sfas 28 TNF-α 29 G-CSF 30 MIP-1β 31 MMP-3 32 IL-15 33 IL-12 (p40) 34IL-2 35 sICAM-1 36 IL-1β 37 GM-CSF 38 IL-1ra 39 VEGF 40 GLP-1 41 Amylin(Total) 42 IL-1α 43 Insulin 44 IL-6 45 TGF-α

Table 11 lists biomarkers whose expression levels have a significant ormarginally significant difference between the LC v. NO femalepopulations. Significance was determined as shown in Examples 1-3 usinga Student's t test. Markers are listed in descending order based on themagnitude of the difference in fluorescence intensity.

TABLE 11 SIGNIFICANT BIOMARKERS FOR NSCLC IN THE FEMALE POPULATION No.Biomarker 1 IL-13 2 EGF 3 IL-12(p70) 4 I-TAC 5 SAA 6 IP-10 7 MMP-1 8MCP-1 9 Eotaxin 10 Leptin 11 MMP-9 12 Adiponectin 13 MMP-7 14 MPO 15IL-8 16 CRP 17 MMP-12 18 MIF 19 SE-selectin 20 PAI-1 21 SAP 22 IL-1ra 23C-Peptide 24 sICAM-1 25 sVCAM-1 26 IL-15 27 G-CSF 28 GM-CSF 29 IFN-γ 30IL-2 31 TGF-α

Table 12 lists biomarkers whose expression levels have a significant ormarginally significant difference between the AST v. LC femalepopulations. Significance was determined as shown in Examples 1-3 usinga Student's t test. Markers are listed in descending order based on themagnitude of the difference in fluorescence intensity.

TABLE 12 SIGNIFICANT BIOMARKERS DISTINGUISHING BETWEEN REACTIVE AIRWAYDISEASE AND NSCLC IN THE FEMALE POPULATION No. Biomarker 1 MMP-7 2 MMP-13 IL-8 4 IL-10 5 SAA 6 HGF 7 I-TAC 8 Leptin 9 Resistin 10 sFSl 11 MPO 12C-Peptide 13 sVCAM-1 14 IL-1α 15 Adiponectin 16 MMP-8 17 IL-15 18 SAP 19MMP-3 20 MMP-9 21 Eotaxin 22 IL-1ra 23 CRP 24 IP-10 25 IL-6 26 MIP-1β 27IL-13 28 IL-5 29 PAI-1 30 IFN-γ

Table 13A lists biomarkers whose expression levels have a significant ormarginally difference between male and female AST populations.Significance was determined as shown in Examples 1-3 using a Student's ttest. Markers are listed in descending order based on the magnitude ofthe difference in fluorescence intensity.

TABLE 13A BIOMARKERS WITH SIGNIFICANT DIFFERENCES BETWEEN MALE ANDFEMALE REACTIVE AIRWAY DISEASE POPULATIONS No. Biomarker 1 IL-6 2 IL-1α3 IL-5 4 G-CSF 5 IL-4 6 IL-7 7 Leptin 8 GM-CSF 9 MIF 10 IL-15 11 TGF-α12 MIP-1β 13 MMP-1 14 sCD40 ligand 15 MMP-2 16 VEGF 17 IL-12 (p40) 18Sfas 19 Resistin 20 I-TAC 21 IL-17 22 HGF 23 MMP-9 24 IP-10 25 CRP 26C-Peptide 27 sVCAM-1 28 PAI-1 29 SAP 30 IL-10 31 Fractalkine 32 Amylin(Total) 33 MPO

Table 13B lists biomarkers whose expression levels have an insignificantdifference between male and female AST populations. Significance wasdetermined as shown in Examples 1-3 using a Student's t test. Markersare listed in descending order based on the magnitude of the differencein fluorescence intensity.

TABLE 13B BIOMARKERS WITH INSIGNIFICANT DIFFERENCES BETWEEN MALE ANDFEMALE REACTIVE AIRWAY DISEASE POPULATIONS No. Biomarkers 1 Adiponectin2 MMP-3 3 IL-1ra 4 IFN-γ 5 SE-selectin 6 IL-2 7 IL-13 8 SAA 9 Eotaxin 10sICAM-1 11 EGF 12 MMP-7 13 IL-12(p70) 14 MMP-12 15 sFSl 16 IL-8 17MMP-13 18 Insulin 19 MMP-8 20 MCP-1 21 GLP-1 22 IL-1β 23 TNF-α 24 MIP-1α

Table 14A lists biomarkers whose expression levels have a significant ormarginally significant difference between male and female LCpopulations. Significance was determined as shown in Examples 1-3 usinga Student's t test. Markers are listed in descending order based on themagnitude of the difference in fluorescence intensity.

TABLE 14A BIOMARKERS WITH SIGNIFICANT DIFFERENCES BETWEEN MALE ANDFEMALE NSCLC POPULATIONS No. Biomarker 1 HGF 2 MMP-1 3 Leptin 4 PAI-1 5Resistin 6 IP-10 7 Adiponectin 8 MIF 9 IL-8 10 IL-10 11 MIP-1α 12 SAA 13I-TAC 14 MMP-3 15 IL-1β

Table 14B lists biomarkers whose expression levels have an insignificantdifference between male and female LC populations. Significance wasdetermined as shown in Examples 1-3 using a Student's t test. Markersare listed in descending order based on the magnitude of the differencein fluorescence intensity.

TABLE 14B BIOMARKERS WITH INSIGNIFICANT DIFFERENCES BETWEEN MALE ANDFEMALE NSCLC POPULATIONS No. Biomarker 1 IL-15 2 Eotaxin 3 Fractalkine 4sICAM-1 5 IL-1ra 6 GM-CSF 7 IL-12 (p40) 8 TGF-α 9 MPO 10 IL-13 11 MMP-712 IL-17 13 IL-2 14 SAP 15 IFN-γ 16 sVCAM-1 17 CRP 18 MCP-1 19 VEGF 20C-Peptide 21 G-CSF 22 Sfas 23 IL-6 24 SE-selectin 25 EGF 26 MMP-9 27Insulin 28 MMP-8 29 GLP-1 30 IL-5 31 MMP-2 32 IL-4 33 MIP-1β 34IL-12(p70) 35 sCD40 ligand 36 IL-1α 37 IL-7 38 MMP-12 39 TNF-α 40 Amylin(Total) 41 sFSl 42 MMP-13

Table 15A lists biomarkers ranked, in ascending order, by the relativestandard deviation in fluorescence intensity for the normal population.

TABLE 15A BIOMARKERS RANKED BY RELATIVE STANDARD DEVIATION INFLUORESCENCE INTENSITY FOR THE NORMAL POPULATION No. Biomarker 1 G-CSF 2IL-15 3 Fractalkine 4 TGF-α 5 SAP 6 IL-10 7 VEGF 8 IL-12 (p40), free 9sVCAM-1 10 IL-17 11 TNF-α 12 MMP-3 13 IFN-γ 14 IL-1β 15 C-Peptide 16IL-7 17 GM-CSF 18 MIP-1β 19 sICAM-1 20 MMP-7 21 IL-4 22 MCP-1 23Adiponectin 24 MIP-1α 25 Resistin 26 CRP 27 SE-selectin 28 IL-1ra 29IL-5 30 Eotaxin 31 PAI-1 32 sFSl 33 Leptin 34 IL-6 35 MMP-9 36 IP-10 37Insulin 38 EGF 39 MMP-1 40 GLP-1 41 SAA 42 IL-1α 43 MIF 44 MMP-12 45Amylin (Total) 46 Sfas 47 MPO 48 IL-8 49 sCD40 ligand 50 MMP-2 51 HGF 52MMP-13 53 IL-2 54 MMP-8 55 IL12 p40 56 IL-2 57 I-TAC

Table 15B lists biomarkers ranked, ascending order, by the relativestandard deviation in fluorescence intensity for the normal femalepopulation.

TABLE 15B BIOMARKERS RANKED BY RELATIVE STANDARD DEVIATION INFLUORESCENCE INTENSITY FOR THE NORMAL FEMALE POPULATION No. Biomarker 1G-CSF 2 IL-15 3 GM-CSF 4 IL-1ra 5 Fractalkine 6 IL-10 7 IL-2 8 TGF-α 9VEGF 10 IL-12 (p40) 11 SAP 12 TNF-α 13 sVCAM-1 14 IL-17 15 MMP-3 16 IL-717 MIP-1β 18 C-Peptide 19 sICAM-1 20 IFN-γ 21 MMP-7 22 IL-1β 23 IL-4 24Adiponectin 25 Resistin 26 Sfas 27 MCP-1 28 CRP 29 SE-selectin 30 MIP-1α31 sFSl 32 Eotaxin 33 PAI-1 34 IP-10 35 IL-5 36 MMP-2 37 MMP-9 38 IL-639 MMP-1 40 EGF 41 IL-12(p70) 42 MIF 43 Leptin 44 sCD40 ligand 45 HGF 46Insulin 47 MPO 48 SAA 49 GLP-1 50 IL-1α 51 MMP-8 52 I-TAC 53 IL-8 54MMP-12 55 IL-13 56 Amylin (Total) 57 MMP-13

Table 15C lists biomarkers ranked, in ascending order, by the relativestandard deviation in fluorescence intensity for the normal malepopulation.

TABLE 15C BIOMARKERS RANKED BY RELATIVE STANDARD DEVIATION INFLUORESCENCE INTENSITY FOR THE NORMAL MALE POPULATION No. Biomarker 1IL-1β 2 IL-15 3 G-CSF 4 MIP-1α 5 TGF-α 6 Fractalkine 7 SAP 8 IFN-γ 9IL-10 10 sVCAM-1 11 TNF-α 12 VEGF 13 IL-12 (p40) 14 MCP-1 15 MIP-1β 16C-Peptide 17 MMP-3 18 IL-17 19 IL-7 20 sICAM-1 21 MIF 22 GM-CSF 23 MMP-724 IL-4 25 Adiponectin 26 SE-selectin 27 CRP 28 Resistin 29 MMP-8 30 HGF31 Leptin 32 IL-5 33 Eotaxin 34 MMP-9 35 IL-1ra 36 PAI-1 37 sFSl 38 IL-639 Insulin 40 EGF 41 Amylin (Total) 42 MMP-1 43 IL-8 44 IP-10 45 SAA 46GLP-1 47 MMP-12 48 IL-1α 49 MMP-13 50 sCD40 ligand 51 MMP-2 52 Sfas 53MPO 54 IL-2 55 I-TAC 56 IL-12(p70) 57 IL-13

Table 16A lists biomarkers whose expression levels have a significantdifference between at least one of AST v. NO male populations, LC v. NOmale populations, and AST v. LC male populations. Significance wasdetermined as shown in Example 4 using the Kruskal-Wallis method.Marginally significant biomarkers are not included. Markers are listedin descending order based on the significance and magnitude of thedifference in fluorescence intensity.

TABLE 16A SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE MALE POPULATIONNo. Biomarker 1 HGF 2 MMP-8 3 I-TAC 4 EGF 5 PAI-1 6 MMP-1 7 MPO 8 MIF 9Eotaxin 10 MMP-12 11 SAA 12 Resistin 13 sFSl 14 Leptin 15 C-Peptide 16MMP-9 17 MCP-1 18 MMP-3 19 MIP-1α 20 MMP-13 21 G-CSF 22 IFN-γ 23 MMP-724 IP-10 25 CRP 26 Insulin 27 VEGF 28 SAP 29 Adiponectin 30 sVCAM-1 31Sfas 32 IL-1ra 33 IL-12 (p40) 34 MIP-1β 35 sICAM-1

Table 16B lists biomarkers whose expression levels have a significantdifference between the AST v. NO male populations, LC v. NO malepopulations, and AST v. LC male populations. Significance was determinedas shown in Example 4 using the Kruskal-Wallis method. Marginallysignificant biomarkers are not included. Markers are listed indescending: order based on the magnitude of the difference influorescence intensity

TABLE 16B SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE MALE POPULATIONNo. Biomarker 1 HGF 2 MMP-8 3 I-TAC 4 EGF 5 PAI-1 6 MMP-1 7 MPO 8 MIF 9Eotaxin 10 MMP-12 11 SAA 12 Resistin 13 sFSl 14 Leptin 15 C-Peptide

Table 16C lists biomarkers whose expression levels have a significantdifference between the AST v. NO male populations and LC NO malepopulations. S canoe was determined as shown in Example 4 using theKruskal-Wallis method. Marginally significant biomarkers are notincluded. Markers are listed in descending order based on die magnitudeof the difference in fluorescence intensity.

TABLE 16C SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE MALE POPULATIONNo. Biomarker 1 HGF 2 MMP-8 3 I-TAC 4 MMP-9 5 EGF 6 PAI-1 7 MMP-1 8 MPO9 MIF 10 MCP-1 11 Eotaxin 12 MMP-3 13 MIP-1α 14 MMP-12 15 MMP-13 16IP-10 17 VEGF 18 Resistin 19 sFSl 20 C-Peptide 21 Sfas 22 SAA 23 Insulin24 SAP 25 Leptin

Table 17 lists biomarkers whose expression levels have a significantdifference between the AST v. NO male populations. Significance wasdetermined as shown in Example 4 using the Kruskal-Wallis method.Marginally significant biomarkers are not included. Markers are listedin descending order based on the magnitude of the difference influoresce intensity.

TABLE 17 SIGNIFICANT BIOMARKERS FOR REACTIVE AIRWAY DISEASE IN THE MALEPOPULATION No. Biomarker 1 HGF 2 I-TAC 3 EGF 4 MMP-8 5 PAI-1 6 MPO 7MMP-9 8 MCP-1 9 MIP-1α 10 Eotaxin 11 MMP-1 12 MIF 13 MMP-3 14 MMP-12 15IP-10 16 sFSl 17 MMP-13 18 VEGF 19 C-Peptide 20 Resistin 21 sVCAM-1 22G-CSF 23 Sfas 24 sICAM-1 25 Leptin 26 SAP 27 Insulin 28 IFN-γ 29 SAA

Table 18 lists biomarkers whose expression levels have a significantdifference between the LC v. NO male populations. Significance wasdetermined as shown in Example 4 using the Kruskal-Wallis method.Marginally significant biomarkers are not included. Markers are listedin descending order based on the magnitude of the difference influorescence intensity.

TABLE 18 SIGNIFICANT BIOMARKERS FOR NSCLC IN THE MALE POPULATION No.Biomarker 1 HGF 2 MMP-8 3 MMP-9 4 I-TAC 5 EGF 6 MMP-1 7 PAI-1 8 MPO 9MIF 10 MMP-3 11 MMP-12 12 Eotaxin 13 MMP-13 14 MCP-1 15 MIP-1α 16 IP-1017 MMP-7 18 Resistin 19 CRP 20 VEGF 21 SAA 22 Adiponectin 23 IL-1ra 24Sfas 25 MIP-1β 26 sFSl 27 C-Peptide 28 Insulin 29 SAP 30 Leptin 31 IL-12(p40) 32

Table 19 lists biomarkers whose expression levels have a significantdifference between the AST v. LC male populations. Significance wasdetermined as shown in Example 4 using the Kruskal-Wallis method.Marginally significant biomarkers are not included. Markers are listedin descending order based on the magnitude of the difference influorescence intensity.

TABLE 19 SIGNIFICANT BIOMARKERS DISTINGUISHING BETWEEN REACTIVE AIRWAYDISEASE AND NSCLC IN THE MALE POPULATION No. Biomarker 1 I-TAC 2 HGF 3MPO 4 sFSl 5 PAI-1 6 C-Peptide 7 sVCAM-1 8 Eotaxin 9 EGF 10 Leptin 11MIF 12 Resistin 13 Adiponectin 14 MMP-12 15 MMP-7 16 CRP 17 G-CSF 18IFN-γ 19 SAA 20 MMP-1 21 MMP-8 22

Table 20A lists biomarkers whose expression levels have a significantdifference between at least one of AST v. NO female populations, LC v.NO female populations, and AST LC female populations. Significance wasdetermined as shown in Example 4 using the Kruskal-Wallis method.Marginally significant biomarkers are not included. Markers are listedin descending order based on the significance and magnitude of thedifference in fluorescence intensity.

TABLE 20A SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE FEMALEPOPULATION No. Biomarker 1 I-TAC 2 PAI-1 3 MMP-7 4 MMP-3 5 IL-8 6 MPO 7Leptin 8 sFSl 9 HGF 10 Resistin 11 C-Peptide 12 MMP-13 13 SAP 14 sVCAM-115 MMP-8 16 IL-10 17 MMP-9 18 G-CSF 19 EGF 20 MCP-1 21 SAA 22 MMP-1 23Fractalkine 24 IL-1α 25 CRP 26 MIP-1β 27 IP-10 28 IL-1ra 29 MIP-1α 30VEGF 31 IFN-γ 32 Adiponectin 33 Eotaxin 34 IL-6 35 MMP-12 36 sICAM-1 37MIF 38 Sfas 39 IL-12 (p40) 40 IL-4 41 Insulin

Table 20B lists biomarkers whose expression levels have a significantdifference between the AST v. NO female populations, LC v. NO femalepopulations, and AST v. LC female populations. Significance wasdetermined as shown in Example 4 using the Kruskal-Wallis method.Marginally significant biomarkers are not included. Markers are listedin descending order based on the magnitude of the difference influorescence intensity.

TABLE 20B SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE FEMALEPOPULATION No. Biomarker 1 I-TAC 2 PAI-1 3 MMP-7 4 MMP-3 5 IL-8 6 MPO 7Leptin 8 sFSl 9 HGF 10 Resistin 11 C-Peptide 12 MMP-13 13 SAP 14 sVCAM-115 MMP-8

Table 20C lists biomarkers whose expression levels have a significantdifference between the AST v. NO female populations and LC v. NO femalepopulations. Significance was determined shown in Example 4 using theKruskal-Wallis method. Marginally biomarkers are not included. Markersare listed in descending order based on the magnitude of the differencein fluorescence intensity.

TABLE 20C SIGNIFICANT BIOMARKERS FOR LUNG DISEASE IN THE FEMALEPOPULATION No. Biomarker 1 MMP-9 2 G-CSF 3 I-TAC 4 EGF 5 MCP-1 6 PAI-1 7SAA 8 MPO 9 MMP-3 10 CRP 11 IP-10 12 Leptin 13 sFSl 14 IFN-γ 15Adiponectin 16 Eotaxin 17 HGF 18 IL-8 19 Resistin 20 IL-6 21 Sfas 22C-Peptide 23 MMP-7 24 sVCAM-1 25 sICAM-1 26 MMP-8 27 MIF 28 MMP-13 29SAP 30 MIP-1α 31 VEGF 32 IL-1ra

Table 21 lists biomarkers whose expression levels have a significantdifference between the AST v. NO female populations. Significance wasdetermined as shown in Example 4 using the Kruskal-Wallis method.Marginally significant biomarkers are not included. Markers are listedin descending order based on the magnitude of the difference influorescence intensity.

TABLE 21 SIGNIFICANT BIOMARKERS FOR REACTIVE AIRWAY DISEASE IN THEFEMALE POPULATION No. Biomarker 1 MMP-9 2 I-TAC 3 EGF 4 PAI-1 5 MCP-1 6G-CSF 7 IL-1α 8 MPO 9 IL-8 10 Leptin 11 sFSl 12 HGF 13 IP-10 14 Resistin15 IFN-γ 16 SAA 17 CRP 18 Adiponectin 19 Eotaxin 20 C-Peptide 21 IL-6 22sVCAM-1 23 IL-4 24 MMP-3 25 Sfas 26 MMP-8 27 sICAM-1 28 MIF 29 MMP-13 30SAP 31 MMP-7 32 MIP-1α 33 VEGF 34 IL-1ra

Table 22 lists biomarkers whose expression levels have a significantdifference between the LC V. NO female populations. Significance wasdetermined as shown in Example 4 using the Kruskal-Wallis method.Marginally significant biomarkers are not included. Markers are listedin descending order based on the magnitude of the difference influorescence intensity.

TABLE 22 SIGNIFICANT BIOMARKERS FOR NSCLC IN THE FEMALE POPULATION No.Biomarker 1 MMP-9 2 G-CSF 3 EGF 4 IL-10 5 MCP-1 6 SAA 7 MMP-3 8 PAI-1 9I-TAC 10 CRP 11 MMP-1 12 MPO 13 IP-10 14 Adiponectin 15 MMP-7 16 Eotaxin17 IFN-γ 18 Leptin 19 MMP-12 20 IL-6 21 Sfas 22 sICAM-1 23 Resistin 24MMP-8 25 sFSl 26 sVCAM-1 27 Fractalkine 28 HGF 29 MIF 30 MMP-13 31C-Peptide 32 SAP 33 Insulin 34 IL-8 35 MIP-1α 36 MIP-1β 37 VEGF 38IL-1ra

Table 23 lists biomarkers whose expression levels have a significantdifference between the AST v. LC female populations. Significance wasdetermined as shown in Example 4 using the Kruskal-Wallis method.Marginally significant biomarkers are not included. Markers are listedin descending order based on the magnitude of the difference influorescence intensity.

TABLE 23 SIGNIFICANT BIOMARKERS DISTINGUISHING BETWEEN REACTIVE AIRWAYDISEASE AND NSCLC IN THE FEMALE POPULATION No. Biomarker 1 IL-8 2 HGF 3sFSl 4 I-TAC 5 C-Peptide 6 IL-1α 7 Resistin 8 IL-12 (p40) 9 Leptin 10sVCAM-1 11 PAI-1 12 MPO 13 MMP-8 14 MMP-12 15 SAP 16 MMP-13 17 MIP-1β 18MMP-1 19 MMP-3 20 Fractalkine 21 MMP-7 22 IL-10

Determining the Extent of Expression

Extent of expression generally relates to a quantitative measurement ofan expression product which is typically a protein or polypeptide. Theinvention contemplates determining the extent of expression at the RNA(pre-transitional) or protein level (which may includepost-translational modification). In particular, the inventioncontemplates determining changes in biomarker concentrations reflectedin an increase or decrease in the level of transcription, translation,post-transcriptional modification, or the extent or degree ofdegradation of protein, where these changes are associated with aparticular disease state or disease progression.

Samples are collected to ensure that the extent of expression in asubject is proportional to the concentration of said biomarker in thesample. Measurements are made so that the measured value is proportionalto the concentration of the biomarker in the sample. Thus, the measuredvalue is proportional to the extent of expression. Selecting samplingtechniques and measurement techniques which meet these requirements iswithin the skill of the art.

Typically, the extent of expression of at least one biomarker indicativeof a lung disease is a level of at least one biomarker that differs by astatistically significant degree from the average expression level innormal individuals; in other words, at least one biomarker isstatistically deviant from the normal. Statistical significance anddeviation may be determined using any known method for comparing meansof populations or comparing a measured value to the mean value for apopulation. Such methods include the Student's t tests for single andmultiple markers considered together, analysis of variance (ANOVA), etc.

As an alternative to, or in combination h determining the extent ofexpression, methods described herein involve determining whether thelevel of a biomarker falls within a normal level (e.g., range) or isoutside the normal level (i.e. abnormal). Those who measure levels ofbiological molecules in physiological samples routinely determine thenormal level of a particular biomarkers in the population they regularlymeasure, typically described as the normal range of values as determinedby the particular laboratory. Thus, the skilled person will inevitablebe familiar with normal levels of a particular biomarker and candetermine whether the level of the biomarker is outside of the normallevel or range.

More typically, the extent of expression of at least one biomarkerindicative of a lung disease is a level of at least: one biomarker alsodiffers by a magnitude sufficient such that the differences areanalytically significant from the average expression level in normalindividuals such that a diagnosis, prognosis, and/or assessment of alung disease may be determined. Those skill in the art understand thatgreater differences in magnitude are preferred to assist in thediagnosis, prognosis, and/or assessment of a lung disease. SeeInstrumental Methods of Analysis, Seventh Edition, 1988.

Many proteins expressed by a normal subject will be expressed to agreater or lesser extent in subjects having a disease or condition, suchas non-small cell lung cancer or asthma. One of skill in the art willappreciate that most diseases manifest changes in multiple, differentbiomarkers. As such, disease may be characterized by a pattern ofexpression a plurality of markers. Indeed, changes in a pattern ofexpression for a plurality of biomarkers may be used in variousdiagnostic and prognostic methods, as well as monitoring, therapyselection, and patient assessment methods. The invention provides forsuch methods. These methods comprise determining a pattern of expressionof a plurality of markers for a particular physiologic state, ordetermining changes in such a pattern which correlate to changes inphysiologic state, as characterized by any technique for suitablepattern recognition.

Numerous methods of determining the extent of expression are known inthe art. Means for determining expression include but are not limited toradio-immuno assay, enzyme-linked immunosorbent assay (ELISA), highpressure liquid chromatography with radiometric or spectrometricdetection via absorbance of visible or ultraviolet light, massspectrometric qualitiative and quantitative analysis, western blotting,1 or 2 dimensional gel electrophoresis with quantitative visualizationby means of detection radioactive, fluorescent or chemiluminescentprobes or nuclei, antibody-based detection with absorptive orfluorescent photometry, quantitation by luminescence of any of a numberof chemiluminescent reporter systems, enzymatic assays,immunoprecipitation or immuno-capture assays, solid and liquid phaseimmunoassays, protein arrays or chaps, DNA arrays or chips, plateassays, assays that use molecules having binding affinity that permitdiscrimination such as aptamers and molecular imprinted polymers, andany other quantitative analytical determination of the concentration ofa biomarker by any other suitable technique, instrumental actuation ofany of the described detection techniques or instrumentation.

The step of determining the extent of expression may be performed by anymeans for determining expression known in the art, especially thosemeans discussed herein. In preferred embodiments, the step ofdetermining the extent of expression comprises performing animmunoassays with antibodies.

Selection of Biomarkers for Determination

One of skill in the art would readily be able to select appropriateantibodies for use in the present invention. The antibody chosenpreferably selective for an antigen of interest, possesses a highbinding specificity for said antigen, and has minimal cross-reactivitywith other antigens. The ability of an antibody to bind to an antigen ofinterest may be determined, for example, by known methods such asenzyme-linked immunosorbent assay (ELISA), now cytometry, andimmunohistochemistry. Preferably, the antigen of interest to which theantibody binds is differentially present in cells or biological samplestaken from diseased patients as opposed to cells or biological samplestaken from healthy patients. The differential presence of the antigen indifferent populations May be determined by comparing the binding of theantibody to samples taken from each of the populations of interest(e.g., the diseased population versus the healthy population). See,e.g., Examples 1-4; see also FIGS. 1-8. For example, the antigen ofinterest may be determined to be expressed at higher levels in cancercells than in non-cancer cells, See, e.g., Examples 1-4; see also FIGS.1-8. Furthermore, the antibody should have a relatively high bindingspecificity for the antigen of interest. The binding specificity of theantibody may be determined by known methods such as immunoprecipitationor by an in vitro binding assay, such as radioimmunoassay (RIA) orELISA. Disclosure of methods for selecting antibodies capable of bindingantigens of interest with high binding specificity and minimalcross-reactivity are provided, for example, in U.S. Pat. No. 7,288,249,which is hereby incorporated by reference in its entirety.

The invention provides for various methods comprising the step ofdetermining the extent of expression of one or more biomarkers describedherein. In one embodiment, the method comprises determining the extentof expression of any of e biomarkers from any number of Tables 1-14 or16-23. The biomarkers in Tables 1-14 and 16-23 are generally listed indecreasing order of the extent of expression. The biomarkers closer tothe top of these Tables generally show more sensitivity (e.g., detectdifferences at lower levels). Using such biomarkers may assist indiscriminating between disease conditions. The biomarkers in Table 15are listed ascending order based on the relative standard deviationfluorescence intensity. The biomarkers closer to the top of Table 15 arealso generally more sensitive due to a lower degree of variance otherthan the variance which is due to the presence of a disease state. Inparticular, these biomarkers have less overall variability and thus arehelpful in reducing background noise when comparing the extent ofexpression of diseased individuals as compared to the extent ofexpression in normal individuals.

Consequently, a preferred method comprises determining the extent ofexpression of biomarker nos. 1-20 of a particular Table, or the totallist of biomarkers if the Table contains less than 20. Alternatively,this mode comprises determining the extent of expression of biomarkernos. 1-10, more preferably biomarker nos. 1-8 even more preferablybiomarker nos. 1-6, and most preferably biomarker nos. 1-4, or a subsetof the biomarkers in any of these groups. In another embodiment, themethod composes determining the extent of expression of any combinationof biomarkers from a particular Table. In another embodiment, the methodcomprises determining the extent of expression of any combination of aplurality of biomarkers from biomarker nos. 1-20 (or the maximum list ifless than 20) of a particular Table, preferably any combination of aplurality of biomarkers from biomarker nos. 1-10, more preferably anycombination of plurality of biomarker; from biomarker nos. 1-8, evenmore preferably any combination of biomarkers from biomarker nos. 1-6,and most preferably any combination of a plurality of biomarkers frombiomarker nos. 1-4, or a subset of the biomarkers in any of thesegroups. In a preferred mode, the method comprises determining the extentof expression of any of a particular subset of three biomarkers selectedfrom biomarker nos. 1-6, 1-8, 1-10, 1-15, or 1-20 of a particular Table.Alternatively, the method comprises determining the extent of expressionof any of a particular subset of four, five, six or seven biomarkersselected from biomarker nos. 1-8, 1-10, 1-15, or 1-20 of a particularTable. Alternatively, the method comprises determining the extent ofexpression of any of a particular subset: of eight, nine, ten, eleven,twelve, or thirteen: biomarkers selected from biomarker nos. 1-15 or1-20 of a particular Table. Of course, the skilled person will recognizethat it is within the contemplation of this invention tocontemporaneously determine the extent of expression of other biomarkerswhether or not associated with the disease of interest.

The determination of expression levels for a plurality of biomarkersfacilitates the observation of pattern of changes in expression, andsuch patterns provide for more sensitive and more accurate diagnosesthan detection of individual biomarkers. For example, a pattern ofchanges would include a plurality of particular biomarkers that aresimultaneously expressed at abnormal levels. A pattern of changes mayalso comprise abnormal elevation of some particular biomarkerssimultaneously with abnormal reduction in other particular biomarkers.The skilled person will observe such patterns in the data presented inthe Figures included herein. (see Discussion in Example 4 below). Suchdetermination may be performed in a multiplex or matrix-based formatsuch as a multiplexed immunoassay.

In another embodiment, the method comprises determining the extent ofexpression of any of the biomarkers from at least two Tables (e.g.,Table 2 and Table 3). In another embodiment, the method comprisesdetermining the extent of expression of biomarker nos. 1-20 (or themaximum list if less than 20) of a particular Table and biomarker nos.1-20 (or the maximum list f less than 20) from a different Table,preferably biomarker nos. 1-10 from one or both Tables, more preferablybiomarker nos. 1-8 from one or both Tables, even more preferablybiomarker nos. 1-6 from one or both Tables, and most preferablybiomarker nos. 1-4 from one or both Tables, or a subset of thebiomarkers in any of these groups. In another embodiment, the methodcomprises determining the extent of expression of any combination of aplurality of biomarkers from a particular Table and a different Table.In another embodiment, the method comprises determining the extent ofexpression of any combination of a plurality biomarkers from biomarkernos. 1-20 (or the minimum list if less than 20) of a particular Tableand any combination of a plurality of biomarkers from biomarker nos.1-20 (or the maximum list if less than 20) from a different Table,preferably any combination of a plurality of biomarkers from biomarkernos. 1-10 from one or both Tables, more preferably any combination of aplurality of biomarkers from biomarker nos. 1-8 from one or both.Tables, even more preferably any combination of a plurality ofbiomarkers from biomarker nos. 1-6 from one or both Tables, and mostpreferably any combination of a plurality of biomarkers from biomarkernos. 1-4 from one or both Tables, or a subset of the biomarkers in anyof these groups. In another embodiment, the plurality of biomarker(s)from one Table are not present in any of the other Tables. In apreferred mode, the method comprises determining the extent ofexpression of any of a particular subset of three biomarkers selectedfrom biomarker nos. 1-6, 1-8, 140, 1-15, or 1-20 of a particular Tableand any of a particular subset of three biomarkers selected frombiomarker nos. 1-6, 1-8, 1-10, 1-15, or 1-20 from a different: Table.Alternatively, the method comprises determining the extent of expressionof any of a particular subset of four, five, six, or seven biomarkersselected from biomarker nos. 1-8 1-10, 1-15, or 1-20 of a particularTable and any of a particular subset of four, five, six, or sevenbiomarkers selected from biomarker nos. 1-8, 1-10, or 1-20 of adifferent Table. Alternatively, the method comprises determining theextent: of expression of any of a particular subset of eight, nine, ten,eleven, twelve, or thirteen biomarkers selected from biomarker nos. 1-15or 1-20 of a particular Table and any of a particular subset of eight,nine, ten, eleven, twelve, or thirteen biomarkers selected frombiomarker nos. 1-15 or 1-20 of a different Table. Of course, the skilledperson will recognize that it is within the contemplation of thisinvention to contemporaneously determine the extent of expression ofother biomarkers whether or not associated with the disease of interest.

It will be understood that the same types of combinations are applicablewhen the method comprises determining the extent of expression of any ofthe biomarkers from at least three different Tables (e.g., Table 2,Table 3, and Table 4). For example, in one embodiment, the methodcomprises determining the extent of expression of any combination of aplurality of biomarkers from biomarker nos. 1-20 or the maximum list ifless than 20) of a first Table, any combination of a plurality ofbiomarkers from biomarker nos. 1-20 (or the maximum list if less than20) from a second Table, and any combination of a plurality ofbiomarkers from biomarker nos. 1-20 (or the maximum list if less than20) of a third Table, preferably any combination of a plurality ofbiomarkers from biomarker nos. 1-10 from each Table, more preferably anycombination of a plurality of biomarkers from biomarker nos. 1-8 fromeach Table, even more preferably any combination of a plurality ofbiomarkers from biomarker nos. 1-6 from each Table, and most preferablyany combination of a plurality of biomarkers from biomarker nos. 1-4from each Table. In a preferred mode, the method comprises determiningthe extent of expression of any of a particular subset of threebiomarkers selected from biomarker nos. 1-6, 1-8, 1-10, 1-15, or 1-20 ofa first Table, any of a particular subset of three biomarkers selectedfrom biomarker nos. 1-6, 1-8 1-10, 1-45, or 1-20 of a second Table, andany a particular subset of three biomarkers selected from biomarker nos.1-6, 1-8, 1-10, 1-15, or 1-20 of a third Table. Alternatively, themethod comprises determining the extent of expression of any of aparticular subset of four, five, six, or seven biomarkers selected frombiomarker nos. 1-8, 1-10, 1-15, or 1-20 of a first Table, any of aparticular subset of tour, five, six, or seven biomarkers selected frombiomarker nos. 1-8, 1-10, 1-15, or 1-20 of a second Table, and any of aparticular subset of four, five, six, or seven biomarkers selected frombiomarker nos. 1 8, 1-10, 1-15, or 1-20 of a third Table. Alternatively,the method comprises determining the extent of expression of any ofparticular subset of eight, nine, ten, eleven, twelve, or thirteenbiomarkers selected from biomarker nos. 1-15 or 1-20 of a first Table,any of a particular subset of eight, nine, ten., eleven, twelve, orthirteen biomarkers selected from biomarker nos. 1-15 or 1-20 of asecond Table, and an of a particular subset of eight, nine, ten, eleven,twelve, or thirteen biomarkers selected from biomarker nos. 1-15 or 1-20of a third Table. Of course, the skilled person will recognize that itis within the contemplation of this invention to contemporaneouslydetermine the extent of expression of other biomarkers whether or notassociated with the disease of interest.

The determination of expression levels for a plurality of biomarkersfacilitates the observation of after changes in expression, and suchpatterns provide for more sensitive and more accurate diagnoses thandetection individual biomarkers. This determination may be performed ina multiple matrix-based format such as a multiplexed immunoassay.

In other embodiments, the extent of expression of no more than 5, 10,15, 20, 25, 30, 35, or 40 are determined.

Selection of biomarkers for use in a diagnostic or prognostic assay maybe facilitated using known relationships between particular biomarkersand their first order interactors. Many, if not all, of the biomarkersidentified by the present inventors (see Tables 1-23) participate invarious communications pathways of the cell or the organism. Deviationof one component of a communication pathway from normal is expected tobe accompanied by related deviations in other members of thecommunication pathway. The skilled worker can readily link members of acommunication pathway using various databases and availablebioinformatics software (see, e.g., ARIADNE PATHWAY STUDIO, Ariadne,Inc., <www.ariaclne.genomics.com> or ChEMBI, Database, EuropeanBioinformatics Institute, European Molecular Biology Laboratory,<www.ebi.ac.uk>). A diagnostic method based on determining whether thelevels of a plurality of biomarkers are abnormal where the plurality ofbiomarkers includes some biomarkers which are not in the samecommunication pathway as others in the plurality is likely to maximizethe information collected by measuring the biomarker levels.

It will also be understood that the various combination of biomarkerspreviously discussed are also applicable to methods for designing kitsand the kits described herein.

It will be appreciated that the selection criteria discussed above,including the preference for selecting particular subsets of markers,may be employed for any of the methods described herein with respect tothose Tables associated with the particular methods.

Methods of Physiological Characterization

The present invention is directed to methods for physiologicalcharacterization of individuals in various populations as describedbelow. As used herein, a method of physiological characterizationaccording to the methods of this invention include methods of diagnosingparticular diseases, methods of predicting the likelihood that anindividual will respond to therapeutic intervention, methods ofmonitoring an individual's reaction to therapeutic intervention, methodsof determining whether an individual is at-risk for an individualdisease, methods for determining the degree of risk for a particulardisease, methods of categorizing a patient's degree of severity ofdisease, and methods for differentiating between diseases having somesymptoms in common. In general, these methods rely on determining theextent of expression of particular biomarkers as described above.

A. General Population

The invention provides for methods of physiological characterization ina subject. In one embodiment, the invention provides for a method ofphysiological characterization in a subject comprising determining; theextent of expression of at least one biomarker from Table 1A in aphysiological ample of the subject where the extent of expression of theat least one biomarker is indicative of lung disease such as reactiveairway disease or non-small cell lung cancer, or assists indistinguishing between reactive airway disease and non-small cell lungcancer, in another embodiment, the method comprises determining theextent of expression of at least one biomarker from Table 1B where theextent of expression of the at least one biomarker is indicative ofreactive airway disease or non-small cell lung cancer, or assists indistinguishing between reactive airway disease and non-small cell lungcancer. In another embodiment, the method comprises determining theextent of expression of at least one biomarker from Table 1C where theextent of expression of the at least one biomarker is indicative ofreactive airway disease or non-small cell lung cancer.

In another embodiment, the method comprises determining the extent ofexpression of SEQ ID NO: 12. In another embodiment, the method comprisesdetermining the extent of expression of SEQ NO: 12 and any one of SEQ IDNOS: 1-11 and 13-17.

In a preferred embodiment, the invention provides for methods ofphysiological characterization in a subject comprising determining theextent of expression of a plurality of biomarkers from Table 1.A in aphysiological sample of the subject, where a pattern of expression ofthe plurality of markers correlate to a physiologic state or condition,or changes in a disease state (e.g., stages in non-small cell lungcancer) or condition. In another preferred embodiment, a pattern ofexpression of a plurality of biomarkers from Table 1A is indicative of alung disease such as non-small cell lung cancer or reactive airwaydisease, or assists in distinguishing between reactive airway disease ornon-small cell lung cancer. Preferably, the plurality of biomarkers areselected based on the low probability of erroneous patternclassification based on the value of Student's t as calculated in theExamples. In another preferred embodiment, patterns of expression ofbiomarkers from Table 1A correlate to an increased likelihood that asubject has or may have a particular disease or condition. In a morepreferred embodiment methods of determining the extent of expression ofa plurality of biomarkers from Table 1A in a subject detect an increasein the likelihood that a subject is developing, has or may have a lungdisease such as non-small cell lung cancer or reactive airway disease(e.g., asthma). Patterns of expression may be characterized by anytechnique known in the art for pattern recognition. The plurality ofbiomarkers may comprise any of the combinations of biomarkers describedabove with respect to Table 1A.

The invention also provides for a method of physiologicalcharacterization in a subject comprising determining the extent ofexpression of SEQ ID NO: 12 in a physiological sample of the subject,wherein the extent of expression of SEQ ID NO: 12 is indicative of thelung disease of non-small cell lung cancer or reactive airway disease.In a preferred embodiment, a pattern of expression of a plurality ofmarkers of SEQ ID NO: 12 and any one of SEQ ID NOS: 1-11 and 13-17 aredetermined and used as described herein.

In another aspect, the invention provides for a method of physiologicalcharacterization in a subject comprising, (a) obtaining a physiologicalsample of the subject; (b) determining the extent of expression in saidsubject of at least one polypeptide selected from the group consistingof SEQ ID NOS: 1-17, and (c) determining the extent of expression insaid subject of at least one biomarker from Table 1A, wherein the extentof expression of both the polypeptide and the biomarker from Table 1A isindicative of a lung disease of non-small cell lung cancer or reactiveairway disease. In another embodiment, a pattern of expression of aplurality of markers of SEQ ID NOS: 1-17, and a plurality of biomarkersfrom Table 1A are determined and used as described herein.

In one embodiment, the subject is at-risk for the lung disease o nailcell cancer or reactive airway disease (e.g., asthma, chronicobstructive pulmonary disease, etc). Subjects “at-risk” include thoseindividuals who are a symptomatic but are more likely than the bulk ofthe population to develop the disease, because of personal or familyhistory, behavior, exposure to disease causing agents (e.g.,carcinogens), or some other reason. “At risk” individuals aretraditionally identified by aggregating the risk factors determined forthe individual. The present invention provides for enhanced detection of“at-risk” individuals by determining the extent of expression ofrelevant biomarkers. In one embodiment, levels of particular biomarkersassociated with the disease (particularly biomarkers from Table 2 orTable 3) are determined for an individual, and levels which differ fromthose expected for the normal population suggest that the individual is“at-risk.” In another embodiment, the number of relevant biomarkers(from Table 2 or Table 3 as appropriate to the disease) which deviatestatistically from normal is determined, with a greater number ofdeviant markers indicating greater risk.

The embodiments described above refer to the biomarkers of Table 1A. Itwill be appreciated, however, that the biomarkers of Table 1B or 1C maybe substituted for the biomarkers of Table 1A in any of the describedembodiments. It will also be appreciated that the plurality ofbiomarkers to be determined in these particular methods may be selectedfrom the identified tables using the criteria discussed above in thesection entitled “Selection of Biomarkers for Determination.”

B. Male Population

The invention provides for a method of physiological characterization ina male subject. In one embodiment, the invention provides for a methodof physiological characterization a male subject comprising obtaining asample from said male subject, and determining the extent of expressionof at least one biomarker from Table 5A or 16A in a physiological sampleof the male subject where the extent of expression of the at least onebiomarker is indicative of lung disease such as reactive airway diseaseor non-small cell lung cancer,or assists in distinguishing betweenreactive airway disease and non-small cell lung cancer. In anotherembodiment, the method comprises determining the extent of expression ofat least one biomarker from Table 5B or 16B where the extent ofexpression of the at least one biomarker is indicative of reactiveairway disease or non-small cell lung cancer, or assists indistinguishing between reactive airway disease and non-small cell lungcancer. In another embodiment, the method comprises determining theextent of expression of at least one biomarker from Table 5C or 16Cwhere the extent of expression of the at least one biomarker isindicative of reactive airway disease or non-small cell lung cancer.

In a preferred embodiment, the invention provides for methods ofphysiological characterization in a male subject comprising determiningthe extent of expression a plurality of biomarkers from Table 5A or 16Ain a physiological sample of the male subject, where a pattern ofexpression of the plurality of markers correlate to a physiologic stateor condition, or changes in a disease state stages in non-small celllung cancer) or condition. In another preferred embodiment, a pattern ofexpression of a plurality of biomarkers from Table 5A or 16A isindicative of a lung disease such as non-small cell lung cancer orreactive airway disease, or assists distinguishing between reactiveairway disease or non-small cell lung cancer. Preferably, the pluralityof biomarkers are selected based on the low probability of erroneouspattern classification based on the value of Student's t as calculatedin the Examples. In another preferred embodiment, patterns of expressionof biomarkers from Table 5A or 16A correlate to an increased likelihoodthat a male subject has or may have a particular disease or condition.In a more preferred embodiment, methods of determining the extent ofexpression of a plurality of biomarkers from Table 5A or 16A in a malesubject detect an increase in the likelihood that a male subject: isdeveloping, has or may have a lung disease such as non-small cell lungcancer or reactive airway disease (e.g., asthma). Patterns of expressionmay be characterized by any technique known in the art for patternrecognition. The plurality biomarkers may comprise any of thecombinations of biomarkers described above with respect to Table 5A or16A,

In another aspect, the invention provides for a method of physiologicalcharacterization in a male subject comprising, (a) obtaining aphysiological sample of the male subject; (b) determining the extent ofexpression in said subject of at least one polypeptide selected from thegroup consisting of SEQ ID NOS: 1-17 and (c) determining be extent ofexpression in said subject of at least one biomarker from Table 5A or16A, wherein the extent of expression of both the polypeptide and thebiomarker from Table 5A or 16A s indicative of a lung disease ofnon-small cell lung cancer or reactive airway disease. In anotherembodiment, a pattern of expression of a plurality of markers of SEQ IDNOS: 1-17, and a plurality of biomarkers from Table 5A or 16A aredetermined and used as described herein.

In one embodiment, the male subject is at-risk for the lung disease ofnon-small cell cancer or reactive airway disease asthma, chronicobstructive pulmonary disease, etc.). “At-risk” subjects and individualsare discussed above. In one embodiment,levels of particular biomarkersassociated with the disease (particularly biomarkers from Tables 6, 7,17 or 18) are determined for an male individual, and levels which differfrom those expected for the normal population suggest that the maleindividual is “at risk.”0 In another embodiment, the number of relevantbiomarkers (from Tables 6, 7, 17 or 18 as appropriate to the disease)which deviate statistically from normal is determined, with a greaternumber of deviant markers indicating greater risk.

The embodiments described above refer to the biomarkers of Table 5A or16A. It will be appreciated, however, that the biomarkers of Table 5B or5C may be substituted for the biomarkers of Table 5A, and that thebiomarkers of Table 16B or 16C may be substituted for the biomarkers ofTable 16A in any of the described embodiments. It will also beappreciated that the plurality of biomarkers to be determined in theseparticular methods may be selected from the identified tables using thecriteria discussed above in the section entitled “Selection ofBiomarkers for Determination.”

C. Female Population

The invention provides for a method of physiological characterization ina female subject. In one embodiment, the invention provides for a methodof physiological characterization in a female subject comprisingobtaining a sample from said female subject, and determining the extentof expression of at least one biomarker from Table 9A or 20A in aphysiological sample of the female subject where the extent ofexpression of the at least one biomarker is indicative of lung diseasesuch as reactive airway disease or non-small cell lung cancer, orassists in distinguishing between reactive airway disease and non-smallcell lung cancer. In another embodiment, the method comprisesdetermining the extent of expression of at least one biomarker fromTable 9B or 20B where the extent of expression the at least onebiomarker is indicative of reactive airway disease or non-small celllung cancer, or assists n distinguishing between reactive airway diseaseand non-small cell lung cancer. In another embodiment, the methodcomprises determining the extent of expression of at least one biomarkerfrom Table 9C or 20C where the extent of expression of the at least onebiomarker is indicative of reactive airway disease or non-small celllung cancer,

in a preferred embodiment, the invention provides for methods ofphysiological characterization in a female subject comprisingdetermining the extent of expression of a plurality of biomarkers fromTable 9A or 20A in a physiological sample of the female subject, where apattern of expression of the plurality of markers correlate to aphysiologic state or condition, or changes in a disease state (e.g.,stages in non-small cell lung cancer) or condition. In another preferredembodiment, a pattern of expression of a plurality of biomarkers fromTable 9A or 20A is indicative of a lung disease such as non-small celllung cancer or reactive airway disease, or assists in distinguishingbetween reactive airway disease or non-small cell lung cancer.Preferably, the plurality of biomarkers are selected based on the lowprobability of erroneous pattern classification based on the valueStudent's t as calculated in the Examples. In another preferredembodiment, patterns of expression of biomarkers from Table 9A or 20Acorrelate to an increased likelihood that a female subject has or mayhave a particular disease or condition. In a more preferred embodiment,methods of determining the extent of expression of a plurality ofbiomarkers from Table 9A or 20A in a female subject detect an increasein the likelihood that a female subject is developing, has or may have alung disease such as non-small cell lung cancer or reactive airwaydisease (e.g., asthma). Patterns of expression may be characterized byany technique known in the art for pattern recognition. The plurality ofbiomarkers may comprise any of the combinations of biomarkers describedabove with respect to Table 9A or 20A.

In another aspect, the invention provides for a method of physiologicalcharacterization in a female subject comprising, (a) obtaining aphysiological sample of the female subject; (b) determining the extentof expression in said subject of at least one polypeptide selected fromthe group consisting of SEQ ID NOS: 1-17, and (c) determining the extentof expression in said subject east one biomarker from Table 9A or 20A,wherein the extent of expression of both the polypeptide and thebiomarker from Table 9A or 20A is indicative of a lung disease ofnon-small cell lung cancer or reactive airway disease. In anotherembodiment, a pattern of expression of a plurality of markers of SEQ IDNOS: 1-17, and a plurality of biomarkers from Table 9A or 20A aredetermined and used as described herein.

In one embodiment, the female subject is at-risk for the lung disease ofnon-small cell cancer or reactive airway disease (e.g., asthma, chronicobstructive pulmonary disease, “At-risk” subjects and individuals arediscussed above. In one embodiment, levels of particular biomarkersassociated with the disease (particularly biomarkers from Tables 10, 11,21, or 2 determined for an female individual, and levels which differfrom those expected for the normal population suggest that the maleindividual is “at-risk.” In another embodiment, the number of relevantbiomarkers (from Tables 10, 11, 21, or 22 as appropriate to the disease)which deviate statistically from normal is determined, with a greaternumber of deviant markers indicating greater risk.

The embodiments described above refer to the biomarkers of Table 9A or20A. It will be appreciated, however, that the biomarkers of Table 9B or9C mar be substituted for the biomarkers of Table 9A, and that thebiomarkers of Table 20B or 20C may be substituted for the biomarkers ofTable 9A in any of the described embodiments. It will also beappreciated that the plurality of biomarkers to be determined in theseparticular methods may be selected from the identified tables using thecriteria discussed above in the section entitled “Selection ofBiomarkers for Determination.”

Lung Disease

The invention provides for various diagnostic and prognostic methods forlung disease. In particular, the invention provides methods ofdiagnosing reactive airway disease and in particular diseases associatedwith over reactive TH₂ and TH₁₇ cells. Reactive airway diseases includeasthma, chronic obstructive pulmonary disease, allergic rhinitis, cysticfibrosis, bronchitis, or other diseases manifesting hyper-reactivity tovarious physiological and/or environmental stimuli. In particular, theinvention provides for methods of diagnosing asthma and chronicobstructive pulmonary disease, more particularly diagnosing asthma.

The invention also provides methods of diagnosing non-small cell lungcancer. These methods include determining the extent of expression of aleast one biomarker described herein, wherein the biomarker(s) isindicative of the presence or development of non-small lung cancer. Forexample, the extent of expression of biomarkers described herein may beused to determine the extent of progression of non-small lung cancer,the presence of pre-cancerous lesions, or staging of non-small lungcancer.

In particular embodiments, the subject: is selected from thoseindividuals who exhibit one or more symptoms of non-small cell lungcancer or reactive airway disease. Symptoms may include cough, shortnessof breath, wheezing, chest pain, and hemoptysis, shoulder pain thattravels down the outside the arm or paralysis the vocal cords leading tohoarseness; invasion of the esophagus may lead to difficulty swallowing.If a large airway is obstructed, collapse of a portion of the lung mayoccur and cause infections leading to abscesses or pneumonia. Metastasesto the bones may produce excruciating pain. Metastases to the brain maycause neurologic symptoms including blurred vision headaches, seizuresor symptoms commonly associated with stroke such as weakness or loss ofsensation in parts of the body. Lung cancers often produce symptoms thatresult from production of hormone-like substances by the tumor cells. Acommon paraneoplastic syndrome seen in NSCLC is the productionparathyroid hormone like substances which cause calcium in thebloodstream to be elevated. Asthma typically produces symptoms such ascoughing, especially at night, wheezing, shortness of breath andfeelings of chest tightness, pain or pressure. Thus, it is apparent thatmany of the symptoms of asthma are common to NSCLC.

Methods of Diagnosing Reactive Airway Disease

The present invention is directed to methods of diagnosing reactiveairway disease in individuals in various populations as described below.In general, these methods rely on determining the extent of expressionof particular biomarkers as described herein.

A. General Population

The Invention provides for a method of diagnosing reactive airwaydisease in a subject comprising, (a) obtaining a physiological sample ofthe subject; and (b) determining the extent of expression in saidsubject of at least one biomarker from Table 2, wherein the extent ofexpression of said at least one biomarker is indicative of reactiveairway disease.

In a preferred embodiment, the invention provides for methods ofdiagnosing reactive airway disease in a subject: comprising determiningthe extent of expression of a plurality of biomarkers from Table 2 in aphysiological sample of e subject, wherein a pattern of expression ofthe plurality of markers are indicative of reactive airway disease orcorrelate to changes in a reactive airway disease state. In anotherpreferred embodiment, patterns of expression relate to an increasedlikelihood that a subject has or may have reactive airway disease.Patterns of expression maybe characterized by any technique known in theart for pattern recognition. The plurality of biomarkers may compriseany of the combinations of biomarkers described above with respect toTable 2. Indeed, it will be appreciated that the plurality of biomarkersto be determined in these particular methods may be selected from theidentified tables using the criteria discussed above in the sectionentitled “Selection of Biomarkers for Determination.”

In one embodiment, the subject is at-risk for reactive airway disease.In one embodiment, levels particular biomarkers associated with reactiveairway disease are determined for an individual, and levels which differfrom those expected for the normal population suggest that theindividual is “at-risk.” In another embodiment, the number of relevantbiomarkers from Table 2 which deviate statistically from normal isdetermined, with a greater number of deviant markers indicating greaterrisk of reactive airway disease. In another embodiment, the subject isselected from those individuals who exhibit one or more symptomsreactive airway disease.

In any of the above embodiments, the preferred biomarkers for use inthis method comprise at least one biomarker from Table 13B. Morepreferably, all of the biomarkers in this embodiment are found in Table13B.

B. Male Population

The invention provides for a method of diagnosing reactive airwaydisease in a male subject comprising, (a) obtaining a physiologicalsample of the male subject; and (b) determining the extent of expressionin said subject of at least one biomarker from Table 6 or 17, whereinthe extent of expression of said at least one biomarker is indicative ofreactive airway disease.

In a preferred embodiment, the invention provides for methods ofdiagnosing reactive airway disease in a male subject comprisingdetermining the extent of expression of a plurality of biomarkers fromTable 6 or 17 in a physiological sample of the male subject, wherein apattern of expression of the plurality of markers are indicative ofreactive airway disease or correlate to changes in a reactive airwaydisease state. In another preferred embodiment, patterns of expressioncorrelate to an increased likelihood that a male subject has or may havereactive airway disease. Patterns of expression may DC characterized byany technique known in the art for pattern recognition. The plurality ofbiomarkers may comprise any of the combinations of biomarkers describedabove with respect to Table 6 or 17. Indeed, it will be appreciated thatthe plurality of biomarkers to be determined in these particular methodsmay be selected from the identified tables using the criteria discussedabove in the section entitled “Selection of Biomarkers forDeterminations.”

In one embodiment, the male subject at-risk for reactive airway disease.In one embodiment, levels of particular biomarkers associated withreactive airway disease are determined for a male individual, and levelswhich differ from those expected for the normal male population suggestthat the individual is “at-risk.” In another embodiment, the number ofrelevant biomarkers from Table 6 which deviate statistically from normalis determined, wit: greater number of deviant markers indicating greaterrisk of reactive airway disease. In another embodiment, the male subjects selected from those individuals who exhibit one or more symptoms ofreactive airway disease.

In another embodiment, the biomarkers for use in this method comprise atleast one biomarker from Table 13A.

C. Female Population

The invention provides for a method of diagnosing reactive airwaydisease in a female subject comprising, (a) obtaining a physiologicalsample of the female subject; and (b) determining the extent ofexpression in said subject of least one biomarker from Table 10 or 21,wherein the extent of expression of said at least one biomarker isindicative of reactive airway disease.

In a preferred embodiment, the invention provides for methods ofdiagnosing reactive airway disease in a female subject comprisingdetermining the extent of expression of a plurality of biomarkers fromTable 10 or 21 in a physiological sample of the female subject, whereina pattern of expression of the plurality of markers are indicative ofreactive airway disease or correlate to changes in a reactive airwaydisease state. In another preferred embodiment patterns of expressioncorrelate to an increased likelihood that a female subject has or mayhave reactive airway disease. Patters of expression may be characterizedby any technique known in the art for pattern recognition. The pluralityof biomarkers may comprise any of the combinations of biomarkersdescribed above with respect to Table 10 or 21. Indeed, it will beappreciated that the plurality of biomarker to be determined in theseparticular methods may be selected from the identified tables using thecriteria discussed above in the section entitled “Selection ofBiomarkers for Determination.”

In one embodiment, the female subject is at-risk for reactive airwaydisease. In one embodiment, levels of popular biomarkers associated withreactive airway disease are determined for a female individual, andlevels which differ from those expected for the normal female populationsuggest that, the it dual is “at-risk.” In another embodiment, thenumber of relevant biomarkers from Table 10 or 21 which deviatestatistically from normal is determined, with a greater number ofdeviant markers indicating greater risk of reactive airway disease. Inanother embodiment, the female subject is selected from thoseindividuals who exhibit one or more symptoms of reactive airway disease.

In another embodiment, the biomarkers for use in this method compose atleast one biomarker from Table 13A.

Methods of Diagnosing Non-Small Cell Lung Cancer

The present invention is directed to methods of diagnosing non-smallcell lung cancer in individuals in various populations as describedbelow. In general, these methods rely on determining the extent ofexpression of particular biomarkers as described herein

A. General Population

The invention provides for a method of diagnosing non-small cell lungcancer in a subject comprising, (a) obtaining a physiological sample ofthe subject; and (b) determining the extent of expression in saidsubject of at least one biomarker from Table 3, wherein the extent ofexpression of said at least one biomarker is indicative of the presenceor development of non-small cell lung cancer.

In a preferred embodiment, the invention provides for methods ofdiagnosing non-small cell lung cancer in a subject comprisingdetermining the extent of expression of a plurality biomarkers fromTable 3 in a physiological sample of the subject, wherein a pattern ofexpression of the plurality of markers are indicative of non-small celllung cancer or correlate to a changes in a non-small cell lung cancerdisease state (i.e., clinical or diagnostic stages). In anotherpreferred embodiment, patterns of expression correlate to an increasedlikelihood that a subject has or may have non-small cell lung cancer.Patterns of expression may be characterized by any technique known inthe art for pattern recognition. The plurality of biomarkers maycomprise any of the combinations of biomarkers described above withrespect to Table 3. Indeed, it will be appreciated that the plurality ofbiomarkers to be determined in these particular methods may be selectedfrom the identified tables using the criteria discussed above in thesection entitled “Selection of Biomarkers for Determination.”

In one embodiment, the subject at-risk for non-small cell lung cancer.In one embodiment, levels of particular biomarkers associated withnon-small cell cancer are determined for an individual, and levels whichdiffer from those expected for the normal population suggest that theindividual is “at-risk.” In another embodiment, the number of relevantbiomarkers from Table 3 which deviate statistically from normal isdetermined, with a greater number of deviant markers indicating greaterrisk of non-small cell cancer. In another embodiment, the subject isselected from those individuals who exhibit one or more symptoms ofnon-small cell lung cancer.

In any of the above embodiments, the preferred biomarkers for use inthis method comprise at least one biomarker from Table 14B. Morepreferably, all of the biomarkers this embodiment are found in Table14B.

B. Male Population

The invention also provides for a method of diagnosing non-small celllung cancer in a male subject comprising, (a) obtaining a physiologicalsample of the male subject; and (b) determining the extent of expressionin said subject of at least one biomarker from Table 7 or 18, whereinthe extent of expression of said at least one biomarker is indicative ofbe presence or development of non-small cell lung cancer.

In a preferred embodiment, the invention provides for methods ofdiagnosing non-small cell lung cancer a male subject comprisingdetermining the extent of expression of a plurality of biomarkers fromTable 7 or 18 in a physiological sample of the male subject, wherein apattern of expression of the plurality of markers are indicative ofnon-small cell lung cancer or correlate to a changes in a non-small celllung cancer disease state (e.g., stages). In another preferredembodiment, patterns of expression correlate to an increased likelihoodthat a subject has or may have no small cell lung cancer. Patterns ofexpression may be characterized by any technique known in the art orpattern recognition. The plurality of biomarkers may comprise any of thecombinations of biomarkers described above with respect to Table 7 or18. Indeed, it will be appreciated that the plurality biomarkers to bedetermined in these particular methods may be selected from theidentified tables using the criteria discussed above in the sectionentitled “Selection of Biomarkers for Determination.”

In one embodiment, the male subject is at-risk for non-small cell lungcancer. In one embodiment, levels of particular biomarkers associatedwith non-small cell cancer are determined for a male individual, andlevels which diiffer from those expected for the normal male populationsuggest that the individual is “at-risk.” In another embodiment, thenumber of relevant biomarkers from Table 7 which deviate statisticallyfrom normal is determined, with a greater number of deviant markersindicating greater risk of non-small cell cancer. In another embodiment,the male subject is selected from those individuals who exhibit one ormore symptoms of non-small cell lung cancer.

In another embodiment, the biomarkers for use in this method comprise atleast one biomarker from Table 14A.

C. Female Population

The invention also provides for a method of diagnosing non-small celllung cancer a female subject comprising, (a) obtaining a physiologicalsample of the female subject; and (b) determining the extent ofexpression in said subject of at least one biomarker from Table 11 or22, wherein the extent of expression of said at least one biomarker isindicative of the presence or development of non-small cell lung cancer.

In a preferred embodiment, the invention provides for methods ofdiagnosing non-small cell lung cancer in a female subject comprisingdetermining the extent of expression of a plurality of biomarkers fromTable 11 or 22 in a physiological sample of the female subject, whereina pattern of expression of the plurality of markers are indicative ofnon-small cell lung cancer or correlate to a changes in a non-small celllung cancer disease state (e.g., stages). In another preferredembodiment, patterns of expression correlate to an increased likelihoodthat a female subject has or may have non small cell lung cancer.Patterns of expression may be characterized by any technique known inthe art for pattern recognition. The plurality of biomarkers maycomprise any of the combinations of biomarkers described above withrespect to Table 11 or 22. Indeed, it will be appreciated that theplurality of biomarkers to be determined in these particular methods maybe selected from the identified tables using the criteria discussedabove in the section entitled “Selection of Biomarkers forDetermination.”

In one embodiment, the female subject is at-risk for non-small cell lungcancer. In one embodiment, levels of particular biomarkers associatedwith non-small cell cancer are determined for a female individual, andlevels which differ from those expected for the normal female populationsuggest that the individual is “at-risk.” In another embodiment, thenumber of relevant biomarkers from Table 11 or 22 which deviatestatistically from normal is determined, with a greater number ofdeviant markers indicating greater risk of non-small cell cancer. Inanother embodiment, the female subject is selected from thoseindividuals who exhibit one or more symptoms of non-small cell lungcancer.

In another embodiment, the biomarkers for use in this method comprise atleast one biomarker from Table 14A.

Methods of Discriminating Between. Non- Cell Lung Cancer and ReactiveAirway Disease

The present invention is directed to methods of diagnosing lung diseasein individuals various populations as described below. In general, thesemethods rely on determining the extent of expression of particularbiomarkers that discriminate between the indication of reactive airwaydisease and non-small cell lung cancer.

A. General Population

The invention also provides for a method of diagnosing a lung disease ina subject comprising determining the extent of expression in said,subject of at least one biomarker from Table 4, wherein the extent ofexpression of said at least one biomarker from Table 4 assists indiscriminating between the indication of reactive airway disease andnon-small cell lung cancer. In one embodiment, the subject has beendiagnosed as having reactive airway disease and/or non-small cell lungcancer. For example, the diagnosis may have been determined by theextent of expression of at least one biomarker a physiological sample ofthe subject, where the extent of expression of the at least onebiomarker is indicative of reactive airway disease and/or non-small celllung cancer.

The invention also provides for a method of diagnosing a lung disease ina subject comprising, (a) obtaining a physiological sample of thesubject; and (b) determining the extent of expression in said subject ofat least one biomarker from Table 4, at least one biomarker from Table2, and at least one biomarker from Table 3, wherein (i) said at leastone biomarker from each of Table 2, Table 3, and Table 4 is notidentical, (ii) the extent of expression of said at least one biomarkerfrom Table 2 and Table 3 is indicative of the lung disease of reactiveairway disease and non-small cell lung cancer, respectively; and (iii)the extent of expression of said at least one biomarker from Table 4assists in discriminating between the indication of non-small cell lungcancer and reactive airway disease. Preferably, the method includes atleast one marker from each Table which is not present in either of theother Tables.

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 4, and preferablyalso a plurality of biomarkers from Table 2, and a plurality ofbiomarkers from Table 3. In another preferred embodiment, patterns ofexpression correlate to an increased likelihood that a subject hasnon-small lung cancer or reactive airway disease. Patterns of expressionmay be characterized by any technique known in the art for patternrecognition. The plurality of biomarkers may comprise any of thecombinations of biomarkers described above with respect to Table 2,Table 3, and Table 4. Indeed, it will be appreciated that the pluralityof biomarkers to be determined in these particular methods may beselected from the identified tables using the criteria discussed abovein the section entitled “Selection of Biomarkers for Determination.”

In one embodiment, the subject is at-risk for non-small cell lung cancerand/or reactive airway disease. In another embodiment, the subject =isselected from those individuals who exhibit one or more symptoms ofnon-small lung cancer and/or reactive airway disease.

The invention also provides a diagnostic method to assist indifferentiating the likelihood that a subject is at-risk of developingor suffering from non-small cell lung cancer or reactive airway diseasecomprising, (a) obtaining a physiological sample of the subject who isat-risk for non-small cell lung cancer or reactive airway disease; and(b) determining the extent of expression in said subject of at least onebiomarker from Table 4, wherein the extent of expression of said atleast one biomarker from Table 4 assists in differentiating thelikelihood that said subject is at risk of non-small cell lung cancer orreactive airway disease.

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 4. In anotherpreferred embodiment, patterns of expression correlate to an increasedlikelihood that a subject has non small lung cancer or reactive airwaydisease. Patterns of expression may be characterized by any techniqueknown in the art for pattern recognition. The plurality of biomarkersmay comprise any of the combinations of biomarkers described above withrespect to Table 4. Indeed, it will be appreciated that the plurality ofbiomarkers to be determined in these particular methods may he selectedfrom the identified tables using the criteria discussed above in thesection entitled “Selection of Biomarkers for Determination.”

In one embodiment, the subject is selected from those individuals whoexhibit one or more symptoms of non-small lung cancer or reactive airwaydisease. Methods of relating to “at-risk” subjects are described aboveand methods related thereto are contemplated herein.

B. Male Population

The invention also provides for a method of diagnosing a lung disease ina male subject comprising determining the extent of expression saidsubject of at least one biomarker from Table 8 or 19, wherein the extentof expression of said at least one biomarker from Table 8 or 19 assistsin discriminating between the indication of reactive airway disease andnon-small cell lung cancer. In one embodiment, the male subject has beendiagnosed as having reactive airway disease and/or non-small cell lungcancer. For example, the diagnosis may have been determined by theextent of expression of at least one biomarker in a physiological sampleof the male subject, where the extent of expression of the at least onebiomarker is indicative of reactive airway disease and/or non-small celllung cancer.

The invention also provides for a method of diagnosing a lung disease ina male subject comprising, (a) obtaining a physiological sample of themale subject; and (b) determining the extent of expression in saidsubject of at least one biomarker from Table 8, at least one biomarkerfrom Table 6, and at least one biomarker from Table 7, wherein (i) saidat least one biomarker from each of Table 6, Table 7, and Table 8 is notidentical, (ii) the extent of expression of said a least one biomarkerfrom Table 6 and Table 7 is indicative of the lung disease of reactiveairway disease and non-small cell lung cancer, respectively; and theextent of expression of said at least one biomarker from Table 8 assistsin discriminating between the indication of non-small cell lung cancerand reactive airway disease. Preferably, the method includes at leastone marker from each Table which is not present in either of the otherTables.

The invention also provides for a method of diagnosing a lung disease ina male subject comprising, (a) obtaining a physiological sample of themale subject; and (b) determining the extent of expression in saidsubject of at least one biomarker from Table 19, at least one biomarkerfrom Table 18, and at least one biomarker Table 17, wherein (i) said atleast one biomarker from each of Table 17, Table 18, and Table 19 is notidentical, (ii) the extent of expressions aid at least one biomarkerfrom Table 17 and Table 18 is indicative (iii) the lung disease ofreactive airway disease and non-small cell lung cancer, respectively and(iii) the extent of expression of said at least one biomarker from Table19 assists in discriminating between the indication of non-small celllung cancer and reactive airway disease. Preferably, the method includesat least one marker from each Table which is not present in either ofthe other

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 8, and preferablyalso a plurality of biomarkers from Table 6, and a plurality ofbiomarkers from Table 7. In another preferred embodiment, patterns ofexpression correlate to an increased likelihood that a male subject hasnon-small lung cancer or reactive -way disease. Patterns of expressionmay be characterized by any technique known in the art for patternrecognition. The plurality of biomarkers may comprise any of thecombinations of biomarkers described above with respect to Table 6,Table 7, and Table 8. Indeed, it will be appreciated that the pluralityof biomarkers to be determined in these particular methods may beselected from the identified tables using the criteria discussed abovein the section entitled “Selection of Biomarkers for Determination.”

In a preferred embodiment, the method comprises determining the extentof expression of a plop-slit biomarkers from Table 19, and preferablyalso a plurality of biomarkers from Table 17, and a plurality ofbiomarkers from Table 18. In another preferred embodiment, patterns ofexpression correlate to an increased likelihood that a male subject hasnon-small lung cancer or reactive a ay disease. Patterns of expressionmay be characterized by any technique known n the art for patternrecognition. The plurality biomarkers may comprise any of thecombinations of biomarkers described above with respect to Table 17,Table 18, and Table 19. Indeed, it will be appreciated that theplurality of biomarkers to be determined ^(in) these particular methodsmay be selected from the identified tables using the criteria discussedabove in the section entitled “Selection of Biomarkers forDetermination.”

In one embodiment, the male subject is at-risk non-small cell lungcancer and/or reactive airway disease. In another embodiment the malesubject is selected from those individuals who exhibit one or moresymptoms of non-small lung cancer and/or reactive airway disease.

The invention also provides a diagnostic method to assist indifferentiating the likelihood that a male subject is at-risk ofdeveloping or suffering from non-small cell lung cancer or reactiveairway disease comprising, (a) obtaining a physiological sample of themale subject: who is at-risk for non-small cell lung cancer or reactiveairway disease; and (b) determining the extent of expression in saidsubject of at least one biomarker from Table 8 or 19, wherein the extentof expression of said a least one biomarker from Table 8 or 19 assistsin differentiating the likelihood that said subject is at risk ofnon-small cell lung cancer or reactive airway disease.

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 8. In anotherpreferred embodiment, patterns c expression correlate to an increasedlikelihood that a male subject has non small lung cancer or reactiveairway disease. Patterns of expression may be characterized by anytechnique known in the art for pattern recognition. The plurality ofbiomarkers may comprise an of the combinations of biomarkers describedabove with respect to Table 8 or 19. Indeed, it will be appreciated thatthe plurality of biomarkers to be determined in these particular methodsmay be selected from the identified tables using the criteria discussedabove in the section entitled “Selection of Biomarkers forDetermination.”

In one embodiment, the male subject is selected from those individualswho exhibit one or more symptoms of non-small lung cancer or reactiveairway disease. Methods of relating to “at-risk” subjects are describedabove and methods related thereto are contemplated herein.

B. Female Population

The invention also provides for a method of diagnosing a lung disease ina female subject comprising determining the extent of expression saidsubject of at least one biomarker from Table 12 or 23, wherein theextent of expression of said at least one biomarker from Table 12 or 23assists in discriminating between the indication of reactive airwaydisease and non-small cell lung cancer. In one embodiment, the femalesubject has been diagnosed as having reactive airway disease and/ornon-small cell lung cancer. For example, the diagnosis may have beendetermined by the extent of expression of at least one biomarker in aphysiological sample of the female subject, where the extent ofexpression of the at least one biomarker is indicative of reactiveairway disease and/or non-small cell lung cancer.

The invention also provides for a method of diagnosing a lung disease ina female subject: comprising, (a) obtaining a physiological sample ofthe female subject; and (b) determining the extent of expression in saidsubject of at least one biomarker from Table 12, at least one biomarkerfrom Table 10, and least one biomarker from Table 11, wherein (i) saidat least one biomarker from each of Table 10, Table 11, and Table 12 isnot identical, (ii) the extent of expression of said at least onebiomarker from Table 10 and Table 11 is indicative of the lung diseaseof reactive airway disease and non-small cell lung cancer, respectively;and (iii) the extent of expression of said at least one biomarker fromTable 12 assists in discriminating between the indication of non-smallcell lung cancer and reactive airway disease. Preferably, the methodincludes at least one marker from each Table which is not present ineither of the other Tables.

The invention also provides for a method of diagnosing a lung disease ina female subject comprising, (a) obtaining a physiological sample of thefemale subject; and (b) determining the extent of expression in saidsubject of at least one biomarker from Table 23, at least one biomarkerfrom Table 21, and at least one biomarker from Table 22, wherein (i)said at least one biomarker from each of Table 21, Table 22, and Table23 is not identical, (ii) the extent of expression of said at least onebiomarker from Table 21 and Table 22 is indicative of the lung diseaseof reactive airway disease and non-small cell lung cancer, respectively;and (iii) the extent of expression of said at least one biomarker fromTable 23 assists in discriminating between the indication of non-smallcell lung cancer and reactive airway disease. Preferably, the methodincludes at least one marker from each Table which is not present ineither of the other Tables.

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 12, and preferablyalso a plurality of biomarkers from Table 10, and a plurality ofbiomarkers from Table 11. In another preferred embodiment, patterns ofexpression correlate to an increased likelihood that a male subject hasnon-small cancer or reactive airway disease. Patterns of expression naybe characterized by any technique known in the art for patternrecognition. The plurality of biomarkers may comprise any of thecombinations of biomarkers described above with respect to Table 10,Table 11, and Table 12. Indeed, it will be appreciated that theplurality of biomarkers to be determined in these particular methods maybe selected from the identified tables using the criteria discussedabove in the section entitled “Selection of Biomarkers forDetermination.”

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 23, and preferablyalso a plurality of biomarkers from Table 21, and a plurality ofbiomarkers from Table 22. In another preferred embodiment, patterns ofexpression correlate to an increased likelihood that a male subject hasnon-small lung cancer or reactive a ay disease. Patterns of expressionmay be characterized by any technique known n the art for patternrecognition. The plurality of biomarkers may comprise any of thecombinations of biomarkers described above with respect to Table 21,Table 22, and Table 23. Indeed, it will be appreciated that theplurality of biomarkers to be determined in these particular methods maybe selected from the identified tables using the criteria discussedabove in the section entitled “Selection of Biomarkers forDetermination.”

In one embodiment, the female subject: is at-risk for non-small celllung cancer and/or reactive airway disease. In another embodiment, thefemale subject is selected from those individuals who exhibit one ormore symptoms of non-small lung cancer and/or reactive airway disease.

The invention also provides a diagnostic method to assist indifferentiating the likelihood that a female subject is at-risk ofdeveloping or suffering from non-small cell lung cancer or reactiveairway disease comprising, (a) obtaining a physiological sample of thefemale subject who is at-risk for non-small cell lung cancer or reactiveairway disease; and (b) determining the extent of expression in saidsubject of at least one biomarker from Table 12 or 23, wherein theextent of expression of said at least one biomarker from Table 12 or 23assists in differentiating the likelihood that said subject is at riskof non-small cell lung cancer or reactive as way disease.

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 12 or 23. Inanother preferred embodiment, patterns of expression correlate to anincreased likelihood tint a female subject has non-small lung cancer orreactive airway disease. Patterns of expression may be characterized byany technique known in the art for pattern recognition. The plurality ofbiomarkers may comprise any of the combinations of biomarkers describedabove with respect o Table 12 or 23. Indeed, it will be appreciated thatthe plurality biomarkers to be determined in these particular methodsmay be selected from the identified tables using the criteria discussedabove in the section entitled “Selection of Biomarkers forDetermination.”

In one embodiment, the female subject is selected from those individualswho exhibit one or more symptoms of non-small lung cancer or reactiveairway disease. Methods of relating to “at-risk” subjects are describedabove and methods related thereto are contemplated herein.

In any of the methods described herein which use biomarkers selectedfrom more than one Table for the purpose of discriminating between,e.g., different disease states or different populations, analysis of theresults for the biomarkers from individuals may be performedsimultaneously or sequentially.

Methods of Monitoring Therapy

The present invention is directed to methods of monitoring therapy inindividuals various populations as described below. In general, thesemethods rely on determining the extend expression of particularbiomarkers.

A. General Population

The invention also provides a method of monitoring a subject comprising(a) determining a first extent of expression in said subject of at leastone biomarker from Table 1A in a sample obtained from the subject; (b)determining a second extent of expression in said subject of said atleast one biomarker from Table 1A using a second sample obtained fromthe subject at a different time than said first extent of expression;and (d) comparing said first extent of expression and said second extentof expression. Typically, the subject has experienced therapeuticintervention be the time the first and second samples were obtained.Detecting of changes in the pattern of expression between the first andsecond determinations may be considered to reflect effects of thetherapeutic intervention. This embodiment is also useful to identifyparticular biomarkers which exhibit changes in their extent ofexpression in response to particular therapeutic interventions.

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 1A. The pluralityof biomarkers may comprise any of the combinations of biomarkersdescribed above with respect to Table 1A. Indeed, it will be appreciatedthat the plurality of biomarkers to be determined in these particularmethods may be selected from the identified tables using the criteriadiscussed above in the section entitled “Selection of Biomarkers forDetermination.”

The embodiments described above refer to the biomarkers of Table 1A. Itwill be appreciated, however, that the biomarkers of Table 1B, Table 1C,Table 2, Table 3, or Table 4 may be substituted for the biomarkers Table1A in any of the described embodiments.

B. Male Population

The invention also provides a method of monitoring a male subjectcomprising determining a first extent of expression in said male subjectof at least one biomarker from Table 5A or 16A in a sample obtained fromthe male subject; (b) determining a second extent of expression in saidmale subject of said at least one biomarker from Table 1A or 16A usingsecond sample obtained from the male subject at a different time thansaid first extent of expression; and (d) comparing said first extent ofexpression and said second extent of expression. Typically, the malesubject has experienced therapeutic intervention between the time thefirst and second samples were obtained. Detecting of changes in thepattern of expression between the first and second determinations may beconsidered to reflect effects of the therapeutic intervention. Thisembodiment is also useful to identify particular biomarkers whichexhibit changes in their extent of expression response to particulartherapeutic interventions.

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 5A or 16A Theplurality biomarkers in comprise any of the combinations of biomarkersdescribed above with respect to Table 5A or 16A. Indeed, it will beappreciated that the plurality of biomarkers to be determined in theseparticular methods may be selected from the identified tables using thecriteria discussed above in the section entitled “Selection ofBiomarkers for Determination.”

The embodiments described above refer to the biomarkers of Table 5A or16A. It will be appreciated, however, that the biomarkers of Table 5B,Table 5C, Table 6, Table 7, Table 8, or Table 16B, Table 16C, Table 17,Table 18, or Table 19 may be substituted for the biomarkers of Table 5Aor 16A in any of the described embodiments.

C. Female Population

The invention also provides a method of monitoring a female subjectcomprising (a) deterinini first extent of expression in said femalesubject of at least one biomarker from Table 9A or 20A in a sampleobtained from the female subject; (b) determining second extent ofexpression in said female subject of said at least one biomarker fromTable 9A or 20A using a second sample obtained from the female subjectat a different time than said first extent of expression; and (d)comparing said first extent of expression and s d second extent ofexpression. Typically, the female subject has experienced therapeuticintervention between the time the first and second samples obtained.Detecting of changes in the pattern of expression between the first andsecond determinations may be considered to reflect effects of thetherapeutic intervention. This embodiment is also useful to identifyparticular biomarkers which exhibit changes in their extent ofexpression in response to particular therapeutic interventions.

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 9A or 20A. Theplurality of biomarkers may comprise any of the combinations ofbiomarkers described above with respect to Table 9A or 20A. Indeed, itwill be appreciated that the plurality of biomarkers to be determined inthese particular methods may be selected from the identified tablesusing the criteria discussed above n the section entitled “Selection ofBiomarkers for Determination.”

The embodiments described above refer to the biomarkers of Table 9A or20A. It will be appreciated, however, that the biomarkers of Table 9B,Table 9C, Table 10, Table 11, Table 12, Table 20B, Table 20C, Table 21,Table 22, or Table 23 may be substituted for the biomarkers of Table 9Aor 20A in any of the described embodiments.

Methods of Predicting A Subject's Response to Therapeutic Intervention

The present invention is directed to methods of predicting a subject'sresponse to therapeutic intervention in various populations as describedbelow. In general, these methods rely on determining the extent ofexpression of particular biomarkers.

A. General Population

The invention also provides a method for predicting a subject's responseto therapeutic intervention comprising, obtaining a physiological sampleof the subject; and (b) determining the extent of expression in saidsubject of at least one biomarker from Table 1A, wherein the extent ofexpression of said at least one biomarker from Table 1A assists inpredicting a subject's response to said therapeutic intervention.Preferred biomarkers for use in this embodiment are those biomarkersshown to be responsive to the therapeutic intervention of interest bymonitoring a population of subjects. This embodiment may also be usedfor selection of those patients more likely to be responsive to therapy.

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 1A. The pluralityof biomarkers may comprise any of the combinations of biomarkersdescribed above with respect to Table 1A. Indeed, it will be appreciatedthat the plurality of biomarkers to be determined in these particularmethods may be selected from the identified tables using the criteriadiscussed above in the section entitled “Selection of Biomarkers forDetermination.”

The embodiments described above refer to the biomarkers of Table 1A. Itwill be appreciated, however, that the biomarkers of Table 1B, Table 1C,Table 2, Table 3, or Table 4 may be substitute be biomarkers of Table 1Ain any of the described embodiments.

B. Male Population

The invention also provides a method for predicting a male subject'sresponse to therapeutic intervention comprising, (a) obtaining aphysiological sample of the male subject; and (b) determining the extentof expression in said male subject of at least one biomarker from Table5A or 16A, wherein the extent of expression of aid at least onebiomarker from Table 5A or 16A assists in predicting a male subject'sresponse to said therapeutic intervention. Preferred biomarkers for usein this embodiment are those biomarkers shown to be responsive to thetherapeutic intervention of interest by monitoring a population of malesubjects. This embodrnent may also be used for selection of those malepatients more likely to be responsive to therapy.

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 5A or 16A. Theplurality of biomarkers may comprise any of the combinations ofbiomarkers described above with respect to Table 5A or 16. Indeed, itwill be appreciated that the plurality of biomarkers to be determined inthese particular methods may be selected from the identified tablesusing the criteria discussed above n the section entitled “Selection ofBiomarkers for Determination.”

The embodiments described above refer to the biomarkers of Table 5A or16A. It will be appreciated, however, that the biomarkers of Table 5B,Table 5C, Table 6, Table 7, Table 8, Table 16B, Table 16C, Table 17,Table 18, or Table 19 may be substituted for the biomarkers of Table 5Aor 16A in any of the described embodiments.

C. Female Population

The invention also provides a method for predicting a female subject'sresponse to therapeutic intervention comprising, (a) obtaining aphysiological sample of the female subject; and (b) determining theextent of expression in said female subject of at least one biomarkerfrom Table 9A or 20A, wherein the extent of expression of said at leastone biomarker from Table 9A or 20A. assists in predicting a femalesubject response to said therapeutic intervention. Preferred biomarkersfor use in this embodiment are those biomarkers shown to be responsiveto the therapeutic intervention of interest by monitoring a populationof female subjects. This embodiment may also be used for selection ofthose female patients more likely to be responsive to therapy.

In a preferred embodiment, the method comprises determining the extentof expression of a plurality of biomarkers from Table 9A or 20A. Theplurality of biomarkers may comprise any of the combinations ofbiomarkers described above with respect to Table 9A or 20A. Indeed, itwill be appreciated that the plurality of biomarkers to be determined inthese particular methods may be selected from the identified tablesusing the criteria discussed above in the section entitled “SelectionBiomarkers for Determination.”

The embodiments described above refer to the biomarkers of Table 9A or20A, it will be appreciated, however, that the biomarkers of Table 9B,Table 9C, Table 10, Table 11, Table 12, Table 20B, Table 20C, Table 21,Table 22, or Table 23 may be substituted for the biomarkers of Table 9Aor 20A in any of the described embodiments.

Methods of Designing Kits A. General Population

The invention also provides a method for designing a kit for assistingin diagnosing lung disease in a subject comprising (a) selecting atleast one biomarker from Table 1A; (b) selecting a means for determiningthe extent of expression of said least one biomarker; and (c) designinga kit comprising said means for determining the extent of expression.

The invention also provides a method for designing a kit for diagnosingnon-small cell lung cancer or reactive airway disease in a subjectcomprising (a) selecting at least one biomarker from Table 1B; (b)selecting a means for determining the extent of expression of said atleast one biomarker; and (c) designing a kit comprising said means fordetermining the extent of expression.

The invention also provides a method for designing a kit for diagnosingnon-small cell lung cancer or reactive airway disease in a subjectcomprising (a) selecting at least one biomarker from Table 1C; (b)selecting a means for determining the extent of expression of said atleast one biomarker; and (c) designing a kit comprising said means fordetermining the extent of expression.

The invention also provides a method for designing a kit for diagnosingreactive airway disease in a subject comprising (a) selecting at leastone biomarker from Table 2; (b) selecting a means for determining theextent of expression of said at least one biomarker; and (c) designing akit comprising said means for determine the extent of expression.

The invention also provides a method for designing a kit for diagnosingnon-small cell tang cancer in a subject comprising (a) selecting atleast one biomarker from Table 3; (b) selecting a means for determiningthe extent of expression of said at least one biomarker; and (c)designing a kit comprising said means for determining the extent ofexpression.

The invention also provides a method for designing a kit for assistingin diagnosing lung disease in a subject comprising (a) selecting atleast one biomarker from Table 4; (b) selecting a means for determiningthe extent of expression of said at least one biomarker; and (c)designing a kit comprising said means for determining the extent ofexpression.

In the above methods, steps (b) and (c) may alternatively be performedselecting detection agents for detecting said at least one biomarker,and (c) designing a kit comprising detection agents for detecting atleast one biomarker.

The invention also provides methods for designing kits comprisingselecting at least one biomarker from more than one Table. For example,the invention provides a method for designing kit comprising selectingat least one biomarker from Table 2 and at least one biomarker fromTable 3. In another example, the invention provides a method fordesigning kit comprising selecting at least one biomarker from Table 2,at least one biomarker from Table 3, and at least one biomarker fromTable 4. It will be understood that these methods also comprise steps(b) and (c) as previously described.

it will be appreciated that the plurality of biomarkers to be determinedin these particular methods may be selected from the identified tablesusing the criteria discussed above in the section entitled “Selection ofBiomarkers for Determination.”

B. Male Population

The invention also provides a method for designing a kit for assistingin diagnosing a lung disease in a male subject comprising (a) selectingat least one biomarker from Table 5A or 16A; (b) selecting a means fordetermining the extent of expression of said at least one biomarker; and(c) designing a kit comprising said means for determining the extent ofexpression.

The invention also provides a method for designing a kit for diagnosingnon-small cell lung cancer or reactive airway disease in a male subjectcomprising (a) selecting at least one biomarker from Table 5B or 16B;(b) selecting a means for determining the extent of expression of said aleast one biomarker; and (c) designing a kit comprising said means fordetermining the extent f expression.

The invention also provides a method for designing a kit for diagnosingnon-small cell lung cancer or reactive airway disease n a male subjectcomprising (a) selecting least one biomarker from Table 5C or 16C; (b)selecting a means for determining the extent of expression of said atleast one biomarker; and (c) designing a comprising means fordetermining the extent of expression.

The invention also provides a method for designing a kit for diagnosingreactive airway disease in a male subject comprising (a) selecting atleast one biomarker from Table 6 or 17; (b) selecting a means fordetermining the extent of expression of said at least one biomarker; and(c) designing a kit comprising said means for determining the extent ofexpression.

The invention also provides a method for designing a kit for diagnosingnon-small cell lung cancer in a male subject comprising (a) selecting atleast one biomarker from Table 7 or 18; (b) selecting a means fordetermining the extent of expression of said at least one biomarker; and(c) designing a kit comprising said means for determining the extent ofexpression.

The invention also provides a method for designing a kit for assistingin diagnosing a lung disease in a male subject comprising (a) selectingat least one biomarker from Table 8 or 19; (b) selecting a means fordetermining the extent of expression of said at least one biomarker; and(c) designing a kit comprising said means for determining the extent ofexpression.

In the above methods, steps (b) and (c) may alternatively be performedby selecting detection agents for detecting said at least one biomarker,and (c) designing a kit comprising detection agents for detecting atleast one biomarker.

The invention also provides methods for designing kits comprisingselecting at least one biomarker from more than one Table. For example,the invention provides a method for designing kit comprising selectingat least one biomarker from Table 6 and at least one biomarker fromTable 7. In another example, the invention provides a method fordesigning kit comprising selecting at least one biomarker from Table 6,at least one biomarker from Table 7, and at least one biomarker fromTable 8. In another example, the invention provides a method fordesigning kit comprising selecting at least one biomarker from Table 17and at least one biomarker from Table 18. In another example, theinvention provides a method for designing kit comprising selecting atleast one biomarker from Table 17, at least one biomarker from Table 18,and at least one biomarker from Table 19. It will be understood thatthese methods also comprise steps (b) and (c) as previously'described.

It will be appreciated that the plurality of biomarkers to be determinedin these particular methods may be selected from the identified tablesusing the criteria discussed above in the section entitled “Selection ofBiomarkers for Determination.”

C. Female Population

The invention also provides a method for designing a kit for assistingin diagnosing a lung disease in a female subject comprising (a)selecting at least one biomarker from Table 9A or 20A; (b) selecting ameans for determining the extent of expression of said at least onebiomarker; and (c) designing a kit comprising said means for determiningthe extent of expression.

The invention also provides a method for designing a kit for diagnosingnon-small cell lung cancer or reactive airway disease a female subjectcomprising (a) selecting at least one biomarker from Table 9B or 20B;(b) selecting a means for determining the extent of expression of saidat least one biomarker; and (c) designing a kit comprising said meansfor determining the extent of expression.

The invention also provides a method for designing a kit for diagnosingnon-small cell lung cancer or reactive airway disease in a femalesubject composing (a) select least one biomarker from Table 9C or 20C;(b) selecting a means for determining the extent of expression of said aleast one biomarker; and (c) designing a kit comprising said means fordetermining the extent of expression.

The invention also provides a method for designing a kit for diagnosingreactive airway disease m a female subject comprising (a) selecting eastone biomarker from Table 10 or 21; (b) selecting a means for determiningthe extent of expression of said at least one biomarker; and (c)designing a kit comprising said means for determining the extent ofexpression.

The invention also provides a method for designing a kit for diagnosingnon-small cell lung cancer in a female subject comprising selecting atleast one biomarker from Table 11 or 22; (b) selecting a means fordetermining the extent of expression of said at least one biomarker; and(c) designing a kit comprising said means for determining the extent ofexpression.

The invention also provides a method for designing a kit for assistingin diagnosing lung disease in a female subject comprising (a) selectingat least one biomarker from Table 12 or 23; (b) selecting a means fordetermining the extent of expression of aid at least one biomarker; and(c) designing a kit comprising said means for determining the extent ofexpression.

In the above methods, steps (b) and (c) may alternatively be performedby selecting detection agents for detecting said at least one biomarker,and (c) designing a kit comprising said detection agents for detectingat least one biomarker.

The invention also provides methods for designing kits comprisingselecting at least one biomarker from more than one Table. For example,the on provides a method for designing kit comprising selecting at leastone biomarker from Table 10 and at least one biomarker from Table 11. Inanother example, the invention provides a method for designing kitcomprising selecting at least one biomarker from Table 10, at least onebiomarker from Table 11 and at least one biomarker from Table 12. inanother example, the invention provides a method for designing kitcomprising selecting at least one biomarker from Table 21 and at leastone biomarker from Table 22. In another example, the invention providesa method for designing kit comprising selecting at least one biomarkerTable 21, at least one biomarker from Table 22, and at least onebiomarker from Table 23. it will be understood that these methods alsocomprise steps (b) and (c) as previously described.

It will be appreciated that the plurality of biomarkers to be determinedin these particular methods may be selected from the identified tablesus the criteria discussed above in the section entitled “Selection ofBiomarkers for Determination.”

Kits

The invention provides kits comprising means for determining the extentof expression of at least one of the biomarkers described herein. Theinvention also provides kits comprising detection agents for detectingat least one biomarker described herein.

The invention provides a kit comprising means for determining the extentof expression of at least one biomarker from Table 1A. The inventionprovides a kit comprising detection agents for detecting at least onebiomarker from Table 1A.

The invention also provides a kit comprising means for determining theextent of expression ref SEQ ID NO: 12. In one embodiment, the kitcomprises means for determining the extent of expression of SEQ ID NO:12 and any combination of SEQ ID NOS: 1-11 and 13-17.

The invention also provides a kit comprising, detection agents fordetecting SEQ ID NO: 12. In one embodiment, the kit comprises detectionagents for detecting SEQ ID NO: 12 and any combination of SEQ ID NOS:1-11 and 13-17.

The invention also provides a kit comprising means for determining theextent of expression of at least one polypeptide selected from the groupconsisting of SEQ ID NOS: 1-1.7 and means for determining the extent ofexpression of at least one biomarker from Table 1A.

The invention also provides a kit comprising, detection agents fordetecting at least one polypeptide selected from the group consisting ofSEQ ID NOS: 1-17, and detection agents for detecting at least onebiomarker from Table 1A.

The embodiments described above refer to the biomarkers of Table 1A. Itwill be appreciated, however, that the biomarkers of Table 1B, Table 1C,Table 2, Table 3, Table 4, Table 5A, Table 5B, Table 5C, Table 6, Table7, Table 8, Table 9A, Table 9B, Table 9C, Table 10, Table 11, Table 12,Table 16A, Table 16B, Table 16C, Table 17, Table 18, Table 19, Table20A, Table 20B, Table 20C, Table 21, Table 22, or Table 23 may besubstituted for the biomarkers of Table 1A in any of the described kits.

The invention also provides a kit comprising, (a) first means fordetermining the extent of expression of at least one biomarker fromTable 2; and (b) second means for determining the extent of expressionof at least one biomarker from Table 3, wherein said at least onebiomarker from Table 2 and Table 3 are not identical.

The invention also provides a kit comprising, (a) detection agents fordetecting at least one biomarker from Table 2; and (b) detection agentsfor detecting at least one biomarker from Table 3, wherein said at leastone biomarker from Table 2 and Table 3 are not identical.

The invention also provides a kit comprising, (a) first means fordetermining the extent of expression of at least one biomarker fromTable 2; (b) second means for determining the extent of expression of atleast one biomarker from Table 3; and (c) third means for determiningthe extent of expression of at least one biomarker from Table 4, whereinsaid at least one biomarker from Table 2, Table 3, and Table 4 are notidentical.

The invention also provides a kit comprising, (a) detection agents fordetecting at least one biomarker from Table 2; (b) detection agentsdetecting at least one biomarker from

Table 3; and (c) detection agents for detecting at least one biomarkerfrom Table 4, wherein said at least one biomarker from Table 2, Table 3,and Table 4 are not identical.

The embodiments described above refer to the biomarkers of Table 2,Table 3, and Table 4. It will be appreciated, however, chat thebiomarkers of Table 6, Table 7, Table 8, Table 17, Table 18. or Table 19may be substituted for the biomarkers of Table 2, Table 3, and Table 4,respectively, in any of the described kits. Furthermore, it will beappreciated that the biomarkers of Table 10, Table 11, Table 12, Table21, Table 22, or Table 23 may be substituted for the biomarkers of Table2, Table 3, and Table 4, respectively, in any of the described kits.Even further, the skilled person will understand that the inventioncontemplates kits comprising means for detecting any particularcombination of biomarkers described above for any method requiringdetection particular plural of biomarkers. It will also be appreciatedthat the plurality of biomarkers to be determined in these particularkits may be selected from the identified tables us be criteria discussedabove in the section en led “Selection of Biomarkers for Determination”

The following examples are provided to exemplify various modes of theinvention disclosed herein, but they are not intended to limit theinvention in any way.

EXAMPLE 1

Human blood samples were collected from volunteers. Thirty samples werecollected from individuals not known to have either non-small cell lungcancer or asthma. These thirty samples comprise, and are referred toherein as, the “normal population.” Twenty-eight blood samples werecollected from individuals known to have asthma and diagnosed as such bya physician. These twenty-eight samples comprise, and are referred toherein as, the “asthma population.” Thirty blood samples were collectedfrom individuals known to have non-small cell lung cancers and diagnosedas such by a physician. These thirty samples comprise, and are referredto herein as the “lung cancer population.”

Research was performed to select biomarkers for which was believed thataltered expression levels would be associated h lung cancer or asthma.As used herein, “lung cancer” is meant to encompass those lung cancerswhich are known to be non-small celled lung cancers. The followingfifty-nine biomarkers were selected to be tested: CD40, HepatocyteGrowth Factor (“HGF”), I-TAC (“CXCL11”; “chemokine (C-X-C motif) ligand11, ” “interferon-inducible T-cell alpha chemoattractant”), Leptin(“LEP”), Matrix Metalloproteinase (“MMP”) 1, MMP 2, MMP3, MMP 7, MMP 8,MMP 9, MMP 12, MMP 13, CD40 Soluble Ligand (“CD40 Ligand”). EpidermalGrowth Factor (“EFG”), Eotaxin (“CCL11”), Fractalkine, GranulocyteColony Stimulating Factor (“G-CSF”), Granulocyte Macrophage ColonyStimulating Factor (“GM-CSF”), Interferon γ (“IFN γ”), Interleukin(“IL”) 1α, IL-1β, IL-1ra, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10,IL-12(p40), IL-12(p70), IL-13, IL-15, IL-17, IP-10, Monocyte ChemotacticProtein 1 (“MCP-1”), Macrophage Inflammatory Protein (“MIP”) 1α, MIP-1β,Transforming Growth Factor α (“TGF α”), Tumor Necrosis Factor α (“TNFα”), Vascular Endothelial Growth Factor (“VEGF”), Insulin (“Ins”),C-peptide, Glucagon Like Protein-1/amyline (“GLP-1/amylin”), Amylin(total), Glucagon, Adiponectin, Plasminogen Activator Inhibitor 1(“PAI-1”: “Serpin”) (active/total), Resistin (“RETN”; “xcp1”), SolubleFas Ligand (“sFasL”), Macrophage Migration Inhibitory Factor (“MIF”),sE-Selectin, Soluble Vascular Cell Adhesion Molecule (“sVCAM”), SolubleIntracellular Adhesion Molecule (“sICAM”), Myeloperoxidase (“MPO”),C-Reactive Protein (“CRP”), Serum Amyloid A (“SAA”; “SAA1”), and SerumAmyloid P (“SAP”).

Plasma specimens for each of the normal, asthma and lung cancerpopulations were screened for each of the fifty-nine biomarkers bysubjecting the plasma specimens to analysis using Luminex s xMAPtechnology, a quantitative multiplexed immunoassay using automatedbead-based technologies.

Several different assay kits were used with the Luminex xMAP technologyto screen the biomarkers, namely Millipore's Human Cytokine/Chemokine(Cat# MPXIICYTO-60K, Human Endocrine (Cat# HENDO-65K), Human SerumAdipokines (Cat# HADK1-61K), Human Sepsis/Apoptosis (Cat# HSEP-63K),Human Cardiovascular Panel 1 (Cat# HCVD1-67AK) and Human CardiovascularPanel 2 (HCVD2-67BK), R&D Systems, Inc.'s Human Fluorokine MAP ProfilingBase Kit B (Cat# LUB00) and Human Fluorokine MAP MMP Profiling Base Kit(Cat# LMP000). The fluorescence intensity levels resulting from themultiplexed immunoassay were recorded for each of the fifty-ninebiomarkers for each plasma specimen for each population. The recordedfluorescence intensity is proportional to the concentration of thecorresponding biomarker in the sample, and to the extent of itsexpression in the dual. Averages, standard deviations, and relativestandard deviations for fluorescence intensity level associated witheach biomarker each population were calculated. FIGS. 1A through 1C showthe average mean, standard deviation and relative standard deviation foreach biomarker in the normal (NO), non-small cell lung cancer (LC), andasthma (AST) Populations.

Student's t test was then used to characterize inter differences fareach particular biomarker between each population. Mean fluorescenceintensity measurements of each biomarker for the samples from normalpatients were compared to those of the samples from patients sufferingfrom lung cancer and also to those of samples derived from patientssuffering from asthma. FIG. 1D shows the differences between the variouspopulation means for each marker. In addition, die mean fluorescenceintensity measurements the lung cancer patients were compared to themean fluorescence intensity measurements for the asthma patients, andthe significance was evaluated using the Student's t statistic.

Further analysis of the statistical differences for each biomarkerbetween the normal, asthma and lung cancer populations was performed. Tocharacterize the difference in mean expression levels for each biomarkerbetween the populations, Student's t values were calculated using thet-test function available in the Microsoft EXCEL software package. TheEXCEL t-test function was used to calculate die probability associatedwith the Student's t value under an assumption of equal variance using atwo-tailed distribution.

The significance of the difference in expression levels between thepopulations was determined on the criteria that any Student's t valuewith an associated probability smaller than 0.05 was considered to besignificant to indicate the presence of the given pathology, whetherasthma or lung cancer. Using a criterion of 0.05 or less is generallyaccepted in the scientific community. Any Student's t value with anassociated probability larger than 0.1 was considered to beinsignificant to indicate the presence of the given pathology.Furthermore, any Student's t value with an associated probabilitybetween 0.051 and 0.1 was determined to be marginal.

Referring now to FIG. 1E, the Student's t values with an associatedprobability calculated comparing each biomarker for each population isshown should be noted that the Student's t values with an associatedprobability shown in FIG. 1E are calculated on the basis that each ofthe asthma, normal, and lung cancer populations has a single mean and anormal distribution.

The significance of the differences in biomarker expression levels wereused to rank the relative importance of the biomarkers. Those biomarkersthat were found to be most significantly different between pathologieswere classed as relatively more important. The measurements of meanfluorescence intensity were examined, and data for all biomarkers havingintensities that did not depart significantly from the averageintensities of specimens in the other populations were excluded fromfurther analysis. Those biomarkers ha relatively low relative standarddeviation were classed as more significant than those having relativelyhigh standard deviation.

The direction of deviation, i.e. whether the average level of aparticular marker increased or decreased in any pathology relative toany of the other pathologies, was not used to judge the relativesignificance of a particular marker. In this way, a group of biomarkerswas assembled that showed high variability between pathologies,relatively low relative standard deviation and good instrumental detect(defined as non-zero uncorrected mean fluorescence intensity). Thosecalculations were used to test the efficiency of the immunoassay andanalyzed to determine the biomarkers which showed significantdifferences in expression levels between the expression levels of thenormal population, as well as to determine reference ranges which arecharacteristic of and associated with the pathologies of lung cancerand/or asthma.

Still referring to FIG. 1E, the probabilities associated with theStudent's t values were calculated to compare the asthma population tothe normal population. Significant differences between the asthmapopulation and the normal population were determined from the Student'st probability for the biomarkers sE, Selectin, EGF, Leptin, IL-5, PAI-1Resistin, MMP-13, CD40 Ligand sVCAM-1, HGF, C-Peptide, sICAM-1, MMP-7,Adiponectin, GM-CSF and MIF. This determination was made on the basisthat, when comparing the twenty-eight specimens from the asthmapopulation with the thirty specimens from the normal population usingthe Student's t function described herein, the probabilities associatedwith the Student's t value for each these biomarkers was smaller than0.05. Difference was determined to be insignificant between the asthmapopulation and the normal population for the biomarkers CRP, MMP-9,IL-4, IL-1α, SAA, IL-7 and IL-6, as the Student's t probability for eachof these was significantly greater than 0.05.

As also shown in FIG. 1E, the probabilities associated with theStudent's t values were calculated to compare the lung cancer populationto the normal population. Significant difference between the lung cancerpopulation and the normal population was determined from the Student's tprobability for the biomarkers sE-Selectin, EGF, Leptin, IL-5, PAI-1,Resistin, CRP, MMP-9, IL-4, IL-1α, SAA, IL-7, CD40 Ligand, MMP-7 andMMP-12. Again, this determination was made on the basis that, whencomparing the thirty specimens from the lung cancer population with thethirty specimens from the normal population using the Student's functiondescribed herein, the Student's t probability for each of thesebiomarkers was smaller than 0.05. Difference was determined to beinsignificant between the lung cancer population and the normalpopulation for the biomarkers MMP-13, HGF, C-Peptide, sICAM,Adiponectin, GM-CSF, IL-17, TNF α, ITAC and MIF, as the Student's tprobability for each of these biomarkers was significantly greater than0.05.

Three biomarkers had probabilities associated with the Student's tvalues only slightly greater than 0.05 between the lung cancerpopulation and the normal population. Specifically, when comparing thelung cancer population to the normal population, IL-6 had a Student's tprobability of 0.076195528, sVCAM-1 had a Student's t probability of0.08869949, and IL-15 had a Student's T probability of 0.086324372.These biomarkers are regarded as having insignificant difference betweenthe lung cancer population and the normal population. However, due tothe fact that the Student's t probability for these three biomarkers areclose to 0.05, it is possible that each population may significantlyvary between the normal and lung cancer populations.

Finally, as shown in FIG. 1E, further analysis was done by calculatingthe probabilities associated with the Student's t values to compare thelung cancer population to the asthma population. Significant differencebetween the lung cancer population and the asthma population wasdetermined from the Student's t probability for the biomarkerssE-Selectin, EGF, Leptin, IL-5, PAI-5, Resistin, CRP, MMP-9, IL-4, IL1α,SAA, IL-7, IL-6, MMP-13 sVCAM, HGF, C-Peptide, sICAM, Adiponectin,GM-CSF, IL-17, L-15, TNF α and I-TAC. This determination was made on thebasis that, when comparing the thirty specimens from the lung cancerpopulation with the twenty-eight specimens from the asthma populationusing the Student's t function described herein, the Student's tprobability for each of these biomarkers was smaller than 0.05.Difference was determined to be insignificant between the lung cancerpopulation and the asthma population for the biomarkers CD40 Ligand,MMP-12 and MIF, as the Student's t probability for each of thesebiomarkers was significantly greater than 0.05.

EXAMPLE 2

Human blood samples were collected from volunteers. One hundredforty-two samples were collected from individuals not known to haveeither non-small cell lung cancer or asthma. These samples comprise, andare referred to herein as, the “normal population.” One hundred eightblood samples were collected from individuals known to have asthma anddiagnosed as such by a physician. These samples compose, and arereferred to herein as, the “asthma population.” One hundred forty-sixblood samples were collected from individuals known to have non-smallcell lung cancers and diagnosed as such by a physician. These comprise,and are referred to herein as the “lung cancer population.”

The same methods described in Example 1 were performed. FIGS. 2A-2E showthe results obtained. These results provide guidance for selectingsuitable biomarkers for the methods of this invention. In particular,the probability values for particular markers are useful in this regard.

FIG. 2E shows the probability associated with the effectiveness ofvarious biomarkers for discriminating between the physiological state ofdifferent populations. Probability values of 0.1 or less are highlightedon this table to identify biomarkers of interest. Biomarkers used inpreferred methods of this invention will have probability values of 0.05or less, more preferably 0.01, and even more preferably 0.001 or less,

EXAMPLE 3

Human blood samples were collected from volunteers. Two hundred eightyeight samples were collected from individuals not known to have eithernon-small cell lung cancer or asthma. These samples comprise, and are edto herein as, the “normal population.” One hundred eighty blood sampleswere collected from individuals known to have asthma and diagnosed assuch by a physician. These samples comprise, and are referred to hereinas, the “asthma population,” Three hundred sixty blood samples werecollected from individuals known to have non-small cell lung cancers anddiagnosed as such by a physician. These comprise, and are referred toherein as the “lung cancer population.”

The same methods described in Example 1 were performed. A Panomics'Procarta Cytokine kit (Cat# PC1017) was also used. Antibodies for PAI-1and Leptin were used from two different kits. Antibodies for PAI-1^(A)and Leptin were produced by Millipore. Antibodies for RAI-1^(B) wereproduced by Panomics. FIGS. 3A-3E show the results obtained. Theseresults provide guidance for selecting suitable biomarkers for themethods of this invention. In particular, the probability values forparticular markers are useful in this regard.

FIG. 3E shows the probability associated with the effectiveness ofvarious biomarkers for discriminating between the physiological state ofdifferent populations. Probability values of 0.1 or less are highlightedon this table to identify biomarkers of interest. Biomarkers used inpreferred methods of this invention will have probability values of 0.05or less, more preferably 0.01, and even more preferably 0.001 or less.

The data obtained was then segregated and analyzed by sex.

FIGS. 4A-4C show the average fluorescence intensity level of thebiomarkers in the normal (NO), non-small cell lung cancer (LC), andasthma (AST) female population. FIG. 4D shows the percent change in themean of each of the biomarkers in the AST v. NO female populations, LCv. NO female populations, and the AST v. LC female populations. FIG. 4Eshows the probability associated with Student's t values calculated bycomparing the mean fluorescence intensity measured for each biomarker,where the means to be compared are AST v. NO female populations, LC v.NO female populations, and the AST v. LC female populations,respectively.

The same information with respect to the male population is shown inFIG. 5A-5E.

Next, the female a male population data was compared. FIG. 6A shows thepercent change in the mean of each of the biomarkers in the AST malepopulation compared to the AST female population, the LC male populationcompared to the LC female population, and the NO male populationcompared to the NO female population. FIG. 6B shows the probabilityassociated with Student's t values calculated by comparing the meanfluorescence intensity measured for each biomarker in the male andfemale populations from Example 3, where the means to be compared arethe AST male and female populations, LC male and female populations, andthe NO male and female populations, respectively.

EXAMPLE 4

The Kruskal-Wallis test is a well known, non-parametric statisticalmethod. The data obtained from Example 3 was segregated by sex andanalyzed using the Kruskal-Wallis (U test). Markers with probabilityvalues of 0.05 or less were considered significant. Markers showingmarginally significant (probability between 0.051-0.10) andinsignificant differences (probability above 0.1.0) were discarded. Theresults for the retained markers are show in FIGS. 7-8.

FIG. 7A shows the percent change in the mean concentration of each ofthe biomarkers in the LC v. NO female populations, AST v. NO femalepopulations, and the AST v. LC female populations. The scalar sum (i.e.,the sum of the absolute values of the percent change for all threecomparisons) is also provided and was used to rank the biomarkers. FIG.7B shows the probability associated with be Kruskal-Wallis testcalculated by comparing the concentration measured for each biomarker,where the populations to be compared are AST v. NO female populations,LC v. NO female populations, and die AST v. LC female populations,respectively.

The same information with respect to the male population is shown inFIGS. 8A and 8B.

The biomarkers showed unique gender- and disease-specific patterns. Forunisex analysis of LC, 36 markers with an absolute change of at least25% cutoff threshold and 32 markers with at least 50% cutoff wereidentified. For wort markers with at least 25% and 30 with at least 50%cutoff were found. For men, 39 markers were found at least 25% cutoffand 37 at least 50% cutoff. Expression of four markers was unique forwomen with LC compared to NO: IL-8 and serum amyloid P (downregulated),serum amyloid A and C-reactive protein (all upregulated). Five markerswere unique for men with LC compared to NO: insulin (downregulated),matrix metalloproteinases-7 and 8, resistin and hepatocyte growth factor(all unregulated). Three markers showed opposite patterns of expression:(i) VEGF was downregulated in women and upregulated in men with LCcompared to NO; (ii) Leptin was upregulated in women and downregulatedin men; and (iii) and MIP-1a were upregulated in men and downregulatedin women with LC versus NC).

The invention provides for various methods of gender-basedidentification of disease states. For example the invention provides formethods of physiological characterization in a male subject comprisingdetermining whether insulin is downregulated, and/or matrixmetalloproteinases-7 and -8, resistin and hepatocyte growth factor areupregulated. Such patterns are indicative of disease. Assays within thecontemplation of this invention include detecting abnormal up/downregulation of three, four, or five of these biomarkers in a malesubject.

In another example, the invention provides for methods of physiologicalcharacterization in a female subject comprising determining whether IL-8and/or serum amyloid P are downregulated, and/or serum amyloid. A andC-reactive protein are upregulated. Such patterns are indicative ofdisease. Assays within the contemplation of this invention includedetecting abnormal up/down regulation of three or four of thesebiomarkers in a female subject.

EXAMPLE 5

Human blood samples were collected from volunteers. Thirty samples werecollected from individuals not known to have either non-small cell lungcancer or asthma. The individuals known not to have either non-smallcell lung cancer or asthma comprise, and are referred to herein as, the“normal population.” Twenty-eight blood samples were collected fromindividuals known to have asthma and diagnosed as such by a physician.The individuals known to have asthma comprise, and are referred toherein as, the “asthma population.” Thirty blood samples were collectedfrom individuals known to have non-small cell lung cancers and diagnosedas such by a physician. The individuals known to have non-small celllung cancer comprise, and re referred to herein as the “lung cancerpopulation.” Generally, as used herein, the term “lung cancer” or “lungcancers” is meant to refer to non-small cell lung cancers.

Eight to ten plasma specimens from each of the asthma population, normalpopulation and lung cancer population were selected at random to be eachplasma specimen from each population was subjected to a protease ordigesting agent. Trypsin was used as the protease, and is desirable tobe used as a protease because of its ability to make h specific andhighly predictable cleavages due to the fact that trypsin is known tocleave peptide chains at the carboxyl side of the lysine and arginine,except where a proline is present immediately following either thelysine arginine. Although trypsin was used, i s possible to use otherproteases or digesting agents. It is desirable to use a protease, ormixture of proteases, which cleave at least as specifically as trypsin.

The tryptic peptides, which are the peptides left by the trypsin aftercleavage, were then separated from the insoluble matter by subjectingthe specimens to a centrifugation and a capillary liquid chromatography,with an aqueous acetonitrile gradient with 0.1% formic acid using a0.375×180 mm. Supelcosil ABZ+ column on an Eksigent 2D capillary HPLC toeffect chromatographic resolution of the generated tryptic peptides.This separation of the peptides is necessary because the electrosprayionization process is subject to ion co-suppression, wherein ions of atype having a higher proton affinity will suppress ion formation of ionshaving lower proton affinities if they are simultaneously eluting fromthe electrospray emitter, which in this case is co-terminal with the endof the HPLC column.

This methodology allows for the chromatographic separation of the largenumber of peptides produced in the tryptic digestions and helps tominimize co-suppression problems, thereby maximizing chances of theformation of pseudo-molecular ion co-suppression, thereby maximizing ionsampling. The tryptic peptides for each specimen were then subjected toan LC-ESIMS. The LC-ESIMS separated each peptide in each specimen timeby passing the peptides in each specimen through a column of solventsystem consisting of water, acetonitrile and formic acid as describedabove.

The peptides were then sprayed with an electrospray ionization source toionize the peptides and produce the peptide pseudo-molecular ions asdescribed above. The peptides were passed through a mass analyzer in theLC-ESIMS where molecular masses were measured for each peptidepseudo-molecular ion. After passing through the LC-ESIMS, mass spectralreadouts were produced the peptides present in each sample from the massspectral data, namely the intensities, the molecular weights and thetime of elution from a chromatographic column of the peptides. The massspectral readouts are generally graphic illustrations of the peptidepseudo-molecular ion signals recorded by the LC-ESIMS, wherein thex-axis is the measurement of mass to charge ratio, the y-axis is theintensity of the pseudo-molecular ion signal. These data are thenprocessed by a software system that controls the LC-ESIMS and acquiresand stores the resultant data.

Once the mass spectral data was obtained and placed on the mass spectralreadouts, a comparative analysis was performed wherein the mass spectralreadouts of each plasma specimen tested in the LC-ESIMS for eachpopulation was performed, both interpathologically andintrapathalogically. The mass spectral peaks were compared between eachspecimen tested in the normal population. The mass spectral peaks werethen compared between each specimen tested in the asthma population andthe lung cancer population. Once the intrapathological comparisons wereperformed, interpathological comparisons were performed wherein the massspectral readouts for each specimen tested in the LC-ESIMS for theasthma population was compared against each specimen tested in thenormal population. Likewise, the mass spectral readouts for eachspecimen tested in the LC-ESIMS for the lung cancer population wascompared against each specimen tested in the normal population.

Peptides with mass spectral readouts that indicated the peptideintensities were inconsistently differentially expressedintrapathologically or were not substantially altered (less than 10 foldvariance in intensity) when comparing the asthma population or lungcancer population to the normal population were determined to beinsignificant and excluded. Generally, the exclusion criteria usedinvolved comparing the peptide peak intensities for at least half of theidentified characteristic peptides for a given protein across at leastten data sets derived from the analysis of individual patient plasmaspecimens from each pathology. If the intensity of the majority ofpeptide peaks derived from given protein were at least 10 fold higher inintensity for 80% of the plasma data sets, the protein was classed asdifferentially regulated between the two pathologic classes.

However, the identity of the proteins giving rise to the peptides thatwere observed to be differentially regulated were unknown and needed tobe identified. To make the identification of the proteins, peptidepseudo-molecular ion signal intensities were compared across knowndatabases which contain libraries of known proteins and peptides andsuspected proteins and peptides.

The mass spectral readouts of the tryptic digests for each specimen fromeach of the normal, lung cancer and asthma population were inputted intoa known search engine called MASCOT. MASCOT is a search engine known inthe art which uses mass spectrometry data to identify proteins from fourmajor sequencing databases, namely the MSDB, NCBInr, SwissProt and dbESTdatabases. These databases contain information on all proteins of knownsequence and all putative proteins based on observation ofcharacteristic protein transcription initiation regions derived fromgene sequences. These databases are continually checked for accuracy andredundancy and are subject to continuous addition as new protein andgene sequences are identified and published in the scientific and patentliterature.

Search criteria and parameters were inputted into the MASCOT program andthe mass spectral data from the mass spectral readouts for eachpopulation were run through the MASCOT program. The mass spectral dataentered into the MASCOT program were for the A specimens of eachpathology. The MASCOT program then ran the mass spectral data for thepeptides inputted against the sequencing databases, comparing the peakintensities and masses of each peptide to the masses and peakintensities of known peptides and proteins. MASCOT then produced asearch result which returned a candidate list of possible proteinidentification matches, commonly known as “significant matches” for eachsample that was analyzed.

Significant snatches are determined by the MASCOT program by assigning ascore called a “MOWSE score” for each specimen tested. The MOWSE scoreis an algorithm wherein the score is −10*LOG₁₀(P), where P is theprobability that the observed match is a random event, which correlatesinto a significance p value where p is less than 0.05, which is thegenerally accepted standard in the scientific community. MOWSE scores ofapproximately 55 to approximately 66 or greater are generally consideredsignificant. The significance level varies somewhat due to specificsearch considerations and database parameters. The significant matcheswere returned for each peptide run, resulting in a candidate list ofproteins

Next, comparative analysis was performed using the same methodsdescribed in US 20090069189, which is hereby incorporated by referencein its entirety.

The data from the mass spectral readouts were cross checked with thesignificant matches to confirm the raw data, peak identities, chargemultiplicities,isotope distribution and flanking charge states. Areverse search was then performed to add peptides to the candidate listwhich may have been missed by the automated search through the MASCOTprogram. The additional peptides were identified by selecting the “bestmatch” meaning the single protein which substantially matched eachparameter of the peptide compared, performing an in silico digestwherein the tryptic peptides and their respective molecular massescalculated based on the known amino acid or gene sequence of theprotein. These predicted peptide masses were then searched against theraw mass spectral data and any peaks identified were examined andqualified as described above. Then, all of the peptides including thoseautomatically identified by MASCOT and those identified by manualexamination were entered into the mass list: used by MASCOT. The refinedmatch is then used to derive a refined MOWSE score.

As a result of the identification process, the protein Arginase-1 wasdetermined to be significantly differentially expressed between theasthma population, lung cancer population and/or normal population.Other proteins identified using this method are BAC04615, Q6NSC8,CAF17350, Q6ZUD4, Q8N7P1, CAC69571, FERM domain containing protein 4,JCC1445 proteasome endopeptidase complex chain C2 long splice form,Syntaxin 11, AAK13083 and AAK130490. See US 20090069189, which is herebyincorporated by reference in its entirety.

Having identified a specific protein which is consistentlydifferentially expressed in asthma and lung cancer patients, it ispossible to diagnose these pathologies early in the progression of thediseases by subjecting proteins in a patient's plasma to trypticdigestion and analysis by the LC-ESIMS, obtaining the mass spectraldata, and determining whether the mass spectral data includes peaks forone or more of Arginase-1, BAC04615, Q6NSC8, CAF17350, Q6ZUD4, Q8N7P1,CAC69571, FERM domain containing protein 4, JC 1445 proteasomeendopeptidase complex chain C2 long splice form, Syntaxin 11, AAK13083,and AAK130490. The levels of any proteins found in the patient sampleare then compared to the levels found in a normal population.

The amino acid sequence disclosed SEQ NO: 1 is the primary amino acidsequence known as of the date of filing this application for the proteinBAC04615. The amino acid sequence disclosed in SEQ ID NO: 2 is theprimary amino acid sequence known as of the date of tiling thisapplication for the protein Q6NSC8. The amino acid sequence disclosed inSEQ ID NO: 3 is the primary amino acid sequence known as of the date offiling this application for the protein CAF17350. The amino acidsequence disclosed in SEQ ID NO: 4 is the primary amino acid sequenceknown as of the date of filing this application for the protein Q6ZUD4.The amino acid sequence disclosed in SEQ ID NO: 5 is the primary aminoacid sequence known as of the date of filing this application for theprotein FERM domain containing protein 4. The amino acid sequencedisclosed SEQ ID NO: 6 is the primary amino acid sequence known as ofthe date of filing this application for the protein AAK13083. The aminoacid sequence:disclosed in SEQ ID NO: 7 is the primary amino acidsequence known as of the date of filing this application for the proteinQ8N7P1. The amino acid sequence disclosed in SEQ ID NO: 8 is the primaryamino acid sequence known as of the date of filing this application theprotein CAC69571. The amino acid sequence disclosed in SEQ ID NO: 9 isthe primary amino acid sequence known as of the date of filing thisapplication for the protein JCC1445 proteasome endoperidase complexchain C2 long splice. The amino acid sequence disclosed in SEQ ID NO: 10is the primary amino acid sequence known as of the date of filing thisapplication for the protein Syntaxin 11. The amino acid sequencedisclosed in SEQ ID NO: 11 is the primary amino acid sequence known asof the date of filing this application for the protein AAK13049. Theamino acid sequence disclosed in SEQ ID NO: 12 is the primary ammo acidsequence known as of the date of filing this application for the proteinArginase-1.

EXAMPLE 6

Selected tissue specimens from asthma patients was subjected to the samemethods described in Example 5. See also Application No. 61/176,437,hereby incorporated by reference in its entirety.

As a result of the identification process, the following proteins weredetermined to be significantly differentially expressed in the asthmapatient:

Accession Gene or Suggested Function Mowse SEQ ID Number Protein FromLiterature Mass Score NO: Q6ZR64 FLJ46603 hypothetical protein HBV 2339751 13 (Human) preS1-transactivated protein 1 Q8WUX6 AAH19232 expressedin lung tissue 12347 49 14 (Human) Q5YA4 CCDC52 potential role inregulation 11748 51 15 protein of RhoA GTPase fragment Q5T2Z1 DDA3activated by p53 25035 56 16 (Human) OSHU7C cytochrome terminalcomponent of 7241 46 17 c oxidase the mitochondrial chain VIIcrespiratory chain complex; precursor conversion of redox energy to ATP

Having identified five specific proteins which are consistentlydifferentially expressed in asthma patients, it is possible to diagnosethese pathologies early in the progression of the diseases by subjectingproteins m a patient's tissue specimen to tryptic digestion and analysisby the LC-ESIMS, obtaining the mass spectral data, and determiningwhether the mass spectral data includes peaks for one or more of SEQ IDNOS: 13-17. The levels of any proteins found in the patient sample arethen compared to the levels found in a normal population.

EXAMPLE 7 Diagnostic Test for Non-Small Cell Lung Cancer

A sample of a biological fluid is obtained from a patient for whomdiagnostic information is desired. The sample is preferably blood serumor plasma. The concentration in the sample of seven (7) of the following14 biomarkers is determined: IL-13, I-TAC, MCP-1, MMP-1, MPO, HGF,Eotaxin, MMP-9, MMP-7 SAA, Resistin, IL-5, and sVACM-1. The measuredconcentration from the sample for each biomarker is compared to therange of concentrations of that marker found in the same fluid in normalhuman individuals, a population of individuals diagnosed with asthma,and a population of individuals diagnosed with NSCLC. Deviation from thenormal range is indicative of lung disease, and deviation from the rangefor the population of individuals with asthma is indicative of NSCLC.Tests on a patient using biomarkers from the same set of 14 may be usedin analogous procedures for diagnosis of asthma or other reactive airwaydiseases.

EXAMPLE 8 Monitoring Therapy for Non-Small all Cell Lung Cancer

A pretreatment sample of a biological fluid is obtained from a patientwho has been diagnosed with NSCLS before any treatment for the disease.The sample is preferably blood serum or plasma. The concentration in thesample of eight (8) of the following 24 biomarkers is determined: IL-13,EGF, I-TAC, MMP-1, IL-12 (p70), Eotaxin, MMP-8 MCP-1, MPC), IP-10, SAA,HGF, MMP-9, MMP-12, Amylin (Total), MMP-7, IL-6, Adipenectin, IL-10,IL-5, IL-4, SE-selecting, and MIP-1α. The measured concentration fromthe sample for each biomarker may be compared to the range ofconcentrations of that marker found in the same fluid in normal humanindividuals. After the pretreatment sample leas peen taken the patientundergoes therapeutic intervention comprising surgery followed byirradiation. Samples of the same fluid are taken after surgery, butbefore irradiation Additional samples are taken after each irradiationsession. The concentration in each sample of the same eight (8)biomarkers is determined.

Changes in the level of expression of each biomarker are noted andcompared with other symptoms of progression of the disease.

EXAMPLE 9 Selection of Predictive Biomarkers

A pretreatment sample of a biological fluid is obtained from apopulation of patients who have been diagnosed with NSCLS before anytreatment for the disease. The sample is preferably blood serum orplasma. The concentration in the sample of the following 24 biomarkersis determined: IL-13, EGF, I-TAC, MMP-1, IL-12 (p70), Eotaxin, MMP-8,MCP-1, MPO, IP-10, SAA, HGF, MMP-9, MMP12, Amylin (Total), MMP-7,MIL-1β, Adiponect IL-10, IL-5, IL-4, SE-selectin, and MIP-1α. Themeasured concentration from the sample for each biomarker is compared tothe range of concentrations of that marker found in the same fluid innormal human individuals. After the pretreatment sample has been takeneach patient undergoes therapeutic intervention comprising surgeryfollowed by irradiation. Samples of the same fluid are taken aftersurgery, but before irradiation. Additional samples are taken after eachirradiation session. The concentration in each sample of the 24biomarkers is determined. Changes in the level expression of eachbiomarker are rioted and compared with other symptoms of progression ofthe disease. All biomarkers whose level changes after therapy areidentified.

EXAMPLE 10 Selection of Susceptible Patients

A sample of a biological fluid is obtained from a patient who has beendiagnosed with NSCLS. The sample is preferably blood serum or plasma.The concentration in the sample of each of the biomarkers identified inthe previous example is determined, and patients for whom the highestnumber of biomarkers show values deviating from normal are selected fortreatment.

EXAMPLE 11 Diagnostic Test for Non-Small Cell Lung Cancer in MaleSubject

A sample of a biological fluid is obtained from a male patient for whomdiagnostic information is desired. The sample is preferably blood serumor plasma. The concentration in the sample of seven (7) of the following14 biomarkers is determined: 1-TAC, MPO, HGF, MMP-2, MMP-8, Eotaxin,IL-8, MMP-7, sVACM-1 L-10, Adiponectin, SAP, and IFN-γ. The measuredconcentration from the sample for each biomarker is compared to therange of concentrations of that marker found in the same fluid in normalhuman male individuals, a population of male individuals diagnosed withasthma, and a population of male individuals diagnosed with NSCLC.Deviation from the normal range is indicative of lung disease, anddeviation from the range for the population of individuals with asthmais indicative of NSCLC. Tests on a patient using biomarkers from thesame set of 14 may be used in analogous procedures for diagnosis ofasthma or other reactive airway diseases.

EXAMPLE 12 Alternative Test for Non-small Cell Lung Cancer in a MaleSubject

Many, if not all, of the biomarkers identified in Tables 1-15participate in communications pathways of the sort described above. Someof the biomarkers are related to each other as first order interactors.Selection of markers for use in a diagnostic or prognostic assay may befacilitated using known relationships between particular biomarkers andtheir first order interactors. The known communication relationshipsbetween the biomarkers listed on Table 16B can be seen in FIG. 9,generated by the Ariadne system. FIG. 9 shows that first orderinteractors of HGF (Hepatocyte Growth Factor) include sFasL (soluble hasligand), PAI-1 (serpin Plasminogen Activator Inhibitor 1)(active/total), Ins (Insulin; which also includes C-peptide), EGF(Epidermal Growth Factor), MPO (Myeloperoxidase), and MIF (MigrationInhibitory Factor). Other interactors (not first order) include RETN(resistin, exp1), SAA1 (Serum Amyloid A, SAA), CCL11 (Eotaxin), LEP(Leptin) and CXCL11 (Chemokine (C-X-C motif) ligand 11,Interferon-inducible T-cell alpha chemoattractant (I-TAC) orInterferon-gamma-inducible protein 9 (IP-9)). In addition, FIG. 9 showsthat two biomarkers MMP1 and MMP-8 (Matrix Metalloproteinases 1 and 8)are not on a communication pathway with HGF.

One way to maximize the information collected by measuring a selectionof biomarkers, is to select a plurality of biomarkers such thatbiomarkers which are not in the same communication pathway are includedin the collection, Using the list of biomarkers in Table 16B it appearsthat if the levels of at least HGF or another biomarker that is a firstorder interactors with HGF, and MMP-8 are abnormal in a male subject,the likelihood that the subject has lung cancer is much higher. If thelevel of MMP-1 is also abnormal, then the likelihood is even higher.Thus, one method according to the present invention for diagnosing lungcancer a male subject would be to determine the level of at least HGF oranother biomarker that is a first order into actor with HGF, and MMP-8,and the levels compared to the range expected for a normal population tosee of the levels of these biomarkers is abnormal. In a preferred mode,the diagnostic method would also include determining whether the levelof MMP-1 was normal. More preferable, one or more of CXCL11, LEP, SXAIand/or RETN would also be determined, and the levels compared to therange expected for a population of normal individuals. The more of thesebiomarkers which are present at an abnormal level, the more likely thatthe subject has lung cancer.

EXAMPLE 13 Monitoring Therapy for Non-Small Cell Lung Cancer in a Male

A pretreatment sample of a biological fluid is obtained from a malepatient who has been diagnosed with NSCLS before any treatment for thedisease. The sample is preferably blood serum or plasma. Theconcentration in the sample of eight (8) of the following 24 biomarkersis determined: IL-13, I-TAC, EGF, MPO, HFG, MMP-1, MMP-8, MIF, Eotaxin,IL-12 (p70), MCP-1, MMP-9, SAA, IP-10, Amylin (Total), MMP-7 Resistin,IL-6, MIP-1β, TNF-α, IL-8, IL-5, CRP, and IL-10. The measuredconcentration from the sample for each biomarker may be compared to therange of concentrations of that marker found in the same fluid in normalhuman individuals. After the pretreatment sample has been taken thepatient undergoes therapeutic intervention comprising surgery followedby irradiation. Samples of the same fluid are taken after surgery, butbefore irradiation. Additional samples are taken after each irradiationsession. The concentration in each sample of the same eight (8)biomarkers is determined. Changes in the level of expression of eachbiomarker are noted and compared other symptoms of progression of thedisease.

EXAMPLE 14 Selection of Predictive Biomarkers

A pretreatment sample of a biological fluid is obtained from apopulation of male patients who have been diagnosed with NSCLS beforeany treatment for the disease. The sample is preferably blood serum orplasma. The concentration in the sample of the following 24 biomarkersis determined: IL-13, I-TAC, EGF, MPO, HGF, MMP-1, MMP-8, MIF, Eotaxin,IL-12 (p70), MCP-1, MMP-9, SAA, IP-10, Amylin (Total), MMP-7, Resistin,IL-6, MIP-1β, TNF-α, IL-8, IL-5, CRP, and IL-10. The measuredconcentration from the sample for each biomarker is compared to therange of concentrations of that marker found in the same fluid in normalhuman individuals. After the pretreatment sample has been taken eachpatient undergoes therapeutic intervention comprising surgery followedby irradiation. Samples of the same fluid are taken after surgery, butbefore irradiation. Additional samples are taken after each irradiationsession. The concentration in each sample of the 24 biomarkers isdetermined. Changes in the level of expression of each biomarker arenoted and compared with other symptoms of progression of the disease.All biomarkers whose level changes after therapy are identified.

EXAMPLE 15

Selection of Susceptible patients

A sample of a biological fluid is obtained from a male patient who hasbeen diagnosed with NSCLS. The sample is preferably blood serum orplasma. The concentration in the sample of each of the biomarkersidentified in the previous example is determined, and patients for whomthe highest number of biomarkers show values deviating from normal areselected for treatment.

1. A method of physiological characterization in a subject comprisingdetermining the extent of expression of at least one biomarker fromTable 1A, Table 1B, Table 1C, Table 2, Table 3, Table 4, Table 5A, Table5B, Table 5C, Table 6, Table 7, Table 8, Table 9A, Table 9B, Table 9C,Table 10, Table 11, Table 12, Table 16A, Table 16B, Table 16C, Table 17,Table 18, Table 19, Table 20A, Table 20B, Table 20C, Table 21, Table 22,Table 23, or combinations of said Tables in a physiological sample ofsaid subject, wherein the extent of expression of said at least onebiomarker is indicative of a lung disease. 2-3. (canceled)
 4. The methodof claim 1, wherein the physiological characterization is diagnosingreactive airway disease in a subject comprising determining the extentof expression of at least one biomarker from Table 2, Table 6, Table 10,Table 17, or Table 21 in a physiological sample of said subject, whereinthe extent of expression of said at least one biomarker is indicative ofreactive airway disease.
 5. The method of claim 1, wherein thephysiological characterization is diagnosing non-small cell lung cancerin a subject comprising determining the extent of expression in saidsubject of at least one biomarker from Table 3, Table 7, Table 11, Table18, or Table 22 in a physiological sample of said subject, wherein theextent of expression of said at least one biomarker is indicative of thepresence or development of non-small cell lung cancer.
 6. The method ofclaim 1, wherein the physiological characterization is diagnosing a lungdisease in a subject comprising determining the extent of expression ofat least one biomarker from Table 4, Table 8, Table 12, Table 19, orTable 23 in a physiological sample of said subject, wherein the extentof expression of said at least one biomarker assists in diagnosing alung disease.
 7. The method of claim 1, wherein said at least onebiomarker comprises a plurality of biomarkers.
 8. The method of claim 1,wherein said at least one biomarker is selected from Table 1A, Table 1B,Table 1C, Table 2, Table 3, Table 4, or combinations of said Tables,preferably a plurality of biomarkers is selected from biomarker nos.1-20, more preferably biomarker nos. 1-10 of Table 1A, Table 1B, Table1C, Table 2, Table 3, Table 4, or combinations of said Tables.
 9. Themethod of claim 8, further wherein said at least one biomarker is alsofound on Table 13B and/or Table 14B.
 10. The method of claim 1, whereinthe human is male and said biomarker is selected from Table 5A, Table5B, Table 5C, Table 6, Table 7, Table 8, Table 16A, Table 16B, Table16C, Table 17, Table 18, Table 19, or combinations of said Tables,preferably a plurality of biomarkers is selected from biomarker nos.1-20, more preferably biomarker nos. 1-10 of Table 5A, Table 5B, Table5C, Table 6, Table 7, Table 8, or combinations of said Tables.
 11. Themethod of claim 1, wherein the human is female and said at least onebiomarker is selected from Table 9A, Table 9B, Table 9C, Table 10, Table11, Table 12, Table 20A, Table 20B, Table 20C, Table 21, Table 22, Table23, or combinations of said Tables, preferably a plurality of biomarkersis selected from biomarker nos. 1-20, more preferably biomarker nos.1-10 of Table 9A, Table 9B, Table 9C, Table 10, Table 11, Table 12,Table 20A, Table 20B, Table 20C, Table 21, Table 22, Table 23, orcombinations of said Tables.
 12. The method of claim 10, further whereinsaid at least one biomarker is also found on Table 13A and/or Table 14A.13. The method of physiological characterization according to claim 1,further comprising determining the extent of expression of at least onefirst order interactors linked to a biomarker from Table 1A, Table 1B,Table 1C, Table 2, Table 3, Table 4, Table 5A, Table 5B, Table 5C, Table6, Table 7, Table 8, Table 9A, Table 9B, Table 9C, Table 10, Table 11,Table 12, Table 16A, Table 16B, Table 16C, Table 17, Table 18, Table 19,Table 20A, Table 20B, Table 20C, Table 21, Table 22, or Table 23, in aphysiological sample of said subject, wherein the extent of expressionof said at least one first order interactor is indicative of a lungdisease.
 14. The method of claim 1, wherein said lung disease isnon-small cell lung cancer or reactive airway disease.
 15. The method ofclaim 4, wherein said reactive airway disease is asthma.
 16. The methodof claim 1, wherein determining the extent of expression comprisesperforming a quantitative multiplex immunoassay.
 17. The method of claim1, wherein the method further comprises obtaining a physiological sampleof said subject.
 18. The method of claim 1, wherein the physiologicalsample is biological fluid, such as blood serum or plasma.
 19. Themethod of claim 1, wherein the subject is a mammal, such as a human. 20.A method of physiological characterization of a subject comprising (a)step for determining whether the level of MMP-8 in the subject isabnormal; and (b) step for determining whether the level of biomarkerselected from the group consisting of Hepatocyte Growth Factor (HGF),Soluble Fas Ligand (sFasL), PAI-I, Insulin (INS), Epidermal GrowthFactor (EGF), Myeloperoxidase (MPO), Macrophage Migration InhibitoryFactor (MIF), and combinations thereof in the subject is abnormal,wherein abnormal levels of said biomarkers is indicative of a lungdisease.
 21. The method of claim 21, further comprising a step fordetermining whether the level of MMP-1 in the subject is abnormal. 22.The method of claim 20, wherein step (b) comprises determining whetherthe level of HGF in the subject is abnormal.
 23. A method ofphysiological characterization of a subject comprising (a) measuring thelevel of MMP-8 or a first order interactor linked therewith in thesubject; and (b) measuring the level of a biomarker selected from thegroup consisting of HGF, sFasL, PAI-I, INS, EGF, MPO, and MIF or a firstorder interactor linked therewith in the subject; wherein if the levelsaid biomarkers or said first order interactors linked therewith isabnormal, then the subject has an increased likelihood of a lungdisease.
 24. The method of claim 23, further comprising measuring thelevel of MMP-1 or a first order interactor linked therewith in thesubject, wherein if the level said biomarkers or said first orderinteractors linked therewith is abnormal, then the subject has anincreased likelihood of a lung disease.
 25. The method of claim 23,wherein step (b) comprises measuring the level of HGF in the subject.26-36. (canceled)
 37. A kit comprising means for determining the extentof expression of a plurality of biomarkers from Table 1A, Table 1B,Table 1C, Table 2, Table 3, Table 4, Table 5A, Table 5B, Table 5C, Table6, Table 7, Table 8, Table 9A, Table 9B, Table 9C, Table 10, Table 11,Table 12, Table 16A, Table 16B, Table 16C, Table 17, Table 18, Table 19,Table 20A, Table 20B, Table 20C, Table 21, Table 22, Table 23, orcombinations of said Tables. 38-47. (canceled)